A self-synchronization protection method and system for a multi-terminal power distribution network

Abstract

This invention discloses a self-synchronization protection method and system for multi-terminal distribution networks, belonging to the field of protection and control technology for active distribution networks. The method includes: filtering the instantaneous electrical quantity data to obtain current-filtered output values ​​and voltage-filtered output values ​​of the electrical quantities at the distribution network nodes; preprocessing the synchronized current-filtered output value data to obtain grouped current values; determining whether a fault has occurred within or outside the distribution network based on the Pearson correlation coefficient and weighted Pearson correlation coefficient; and controlling the distribution network to perform protection actions according to the fault's location. This invention can determine whether a fault has occurred within or outside the distribution network using the determined Pearson correlation coefficient and weighted Pearson correlation coefficient, thus enabling rapid determination of whether a fault has occurred within or outside the distribution network.

Description

Technical Field

[0001] This invention relates to the field of protection and control technology for active distribution networks, and more specifically, to a self-synchronization protection method and system for multi-terminal distribution networks. Background Technology

[0002] my country is striving to build a new power system with new energy sources as the mainstay. On the distribution network side, the high penetration of distributed power sources, represented by wind and solar power, and the increasing number of ring network structures are transforming traditional distribution networks from radial networks to multi-terminal active networks. This makes common three-stage current protection and fault location methods based on overcurrent principles difficult to apply. Current differential protection, which is maturely used in transmission networks, requires strict synchronous acquisition of electrical quantity data at both ends, making it difficult to widely adopt given the widespread integration of distributed power sources and the increasingly complex distribution network structure. Furthermore, the synchronization method based on satellite clocks (GPS) used in some current smart distribution network demonstration projects requires additional equipment, resulting in high costs, complex structures, and insufficient reliability. Summary of the Invention

[0003] To address the above problems, this invention proposes a self-synchronization protection method for multi-terminal distribution networks, comprising:

[0004] The instantaneous electrical quantity data of each phase of the distribution network node are collected at a preset acquisition frequency and number of sampling points. Based on the instantaneous electrical quantity data, the per-unit value of the effective value of the zero-sequence voltage of the distribution network node is determined. If the per-unit value of the effective value of the zero-sequence voltage is greater than a preset threshold, the instantaneous electrical quantity data is filtered to obtain the current filtered output value and voltage filtered output value of the electrical quantity of the distribution network node.

[0005] Based on the fault time and voltage filter output value of the distribution network, the current filter output value is self-synchronized and adjusted to obtain a synchronized current filter output value. Based on the effective value of the zero-sequence voltage, the synchronized current filter output value data is preprocessed to obtain the grouped current value.

[0006] Based on the grouped current values, the Pearson correlation coefficient and the weighted Pearson correlation coefficient are determined. Based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, it is determined whether a fault occurs within or outside the distribution network. Based on the fault within or outside the distribution network, the distribution network is controlled to perform protection actions.

[0007] Optionally, based on the instantaneous electrical quantity data, the per-unit value of the zero-sequence voltage RMS value of the distribution network node is determined, including:

[0008] Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes;

[0009] The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value.

[0010] Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

[0011] Optionally, a weighted first-order filtering method is used to filter the instantaneous electrical quantity data. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

[0012] Optionally, based on the fault time of the distribution network, the voltage filter output value and the current filter output value are self-synchronized and adjusted, including:

[0013] Determine the initial recording time;

[0014] If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array;

[0015] Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

[0016] Optionally, the synchronized current filter output value is preprocessed, including: performing average calculation, grouping, summation calculation and correction on the current filter output value in sequence.

[0017] Optional, grouped current values, including: mean-low node grouped current values ​​and mean-high node grouped current values.

[0018] Optionally, based on the grouped current values, determine the Pearson correlation coefficient and the weighted Pearson correlation coefficient, including:

[0019] Based on the mean lower node group current value and the mean upper node group current value, generate an upper / lower node discrete signal sequence with corrected current sum;

[0020] The Pearson correlation coefficient and weighted Pearson correlation coefficient of the discrete signal sequence are determined according to a preset algorithm.

[0021] Optionally, based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, the fault within or outside the distribution network is determined, including:

[0022] If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate.

[0023] If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

[0024] Furthermore, this invention also proposes a self-synchronization protection system for multi-terminal distribution networks, comprising:

[0025] The acquisition unit is used to acquire instantaneous electrical quantity data of each phase of the distribution network node at a preset acquisition frequency and number of sampling points. Based on the instantaneous electrical quantity data, the per-unit value of the effective value of the zero-sequence voltage of the distribution network node is determined. If the per-unit value of the effective value of the zero-sequence voltage is greater than a preset threshold, the instantaneous electrical quantity data is filtered to obtain the current filtered output value and voltage filtered output value of the electrical quantity of the distribution network node.

[0026] The data processing unit is used to perform self-synchronization adjustment on the current filter output value based on the fault time and voltage filter output value of the distribution network to obtain a synchronized current filter output value, and to preprocess the synchronized current filter output value data based on the zero-sequence voltage effective value to obtain grouped current values.

[0027] The control unit is used to determine the Pearson correlation coefficient and the weighted Pearson correlation coefficient based on the grouped current values, determine whether a fault occurs in or outside the distribution network based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, and control the distribution network to perform protection actions according to the fault in or outside the distribution network.

[0028] Optionally, the acquisition unit determines the per-unit value of the zero-sequence voltage RMS value of the distribution network node based on the instantaneous electrical quantity data, including:

[0029] Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes;

[0030] The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value.

[0031] Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

[0032] Optionally, the acquisition unit uses a weighted first-order filtering method to filter the instantaneous electrical quantity data. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

[0033] Optionally, the data processing unit performs self-synchronization adjustment of the voltage filter output value and the current filter output value based on the fault time of the distribution network, including:

[0034] Determine the initial recording time;

[0035] If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array;

[0036] Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

[0037] Optionally, the data processing unit preprocesses the synchronized current filter output value, including: performing average calculation, grouping, summation calculation, and correction processing on the current filter output value in sequence.

[0038] Optional, grouped current values, including: mean-low node grouped current values ​​and mean-high node grouped current values.

[0039] Optionally, the control unit determines the Pearson correlation coefficient and the weighted Pearson correlation coefficient based on the grouped current values, including:

[0040] Based on the mean lower node group current value and the mean upper node group current value, generate an upper / lower node discrete signal sequence with corrected current sum;

[0041] The Pearson correlation coefficient and weighted Pearson correlation coefficient of the discrete signal sequence are determined according to a preset algorithm.

[0042] Optionally, the control unit determines whether a fault occurs within or outside the distribution network based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, including:

[0043] If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate.

[0044] If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

[0045] In another aspect, the present invention also provides a computing device, comprising: one or more processors;

[0046] A processor is used to execute one or more programs;

[0047] When the one or more programs are executed by the one or more processors, the method described above is implemented.

[0048] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method described above.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention can determine whether a fault occurs in the distribution network or outside the distribution network by using the determined Pearson correlation coefficient and weighted Pearson correlation coefficient. Therefore, it can quickly determine whether a fault occurs in the distribution network or outside the distribution network. Attached Figure Description

[0050] Figure 1 This is a flowchart of the method of the present invention;

[0051] Figure 2 This is a flowchart of an embodiment of the present invention;

[0052] Figure 3 This is a flowchart of the weighted first-order filtering algorithm according to an embodiment of the present invention;

[0053] Figure 4 This is a flowchart of the self-synchronization adjustment algorithm according to an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of a typical 10kV multi-terminal distribution network used in an embodiment of the present invention.

[0055] Figure 6 This is a waveform diagram of the self-synchronization adjustment algorithm applied in an embodiment of the present invention.

[0056] Figure 7 The zero-sequence voltage amplitude waveform of the bus node after the fault is shown in the case of a phase-a ground short-circuit fault and a transition resistance of 0Ω at F1 in this embodiment of the invention.

[0057] Figure 8 The zero-sequence current amplitude waveform of each line after the fault is shown in the case of a phase-a ground short-circuit fault set at F1 and the transition resistance is 0Ω, which is an application of the present invention.

[0058] Figure 9 This is a structural diagram of the system of the present invention. Detailed Implementation

[0059] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0060] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0061] Example 1:

[0062] This invention provides a self-synchronization protection method for multi-terminal distribution networks, such as... Figure 1 As shown, it includes:

[0063] Step 1: Collect instantaneous electrical quantity data of each phase of the distribution network node at a preset acquisition frequency and number of sampling points. Based on the instantaneous electrical quantity data, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node. If the per-unit value of the effective value of the zero-sequence voltage is greater than a preset threshold, filter the instantaneous electrical quantity data to obtain the current filter output value and voltage filter output value of the electrical quantity of the distribution network node.

[0064] Step 2: Based on the fault time and voltage filter output value of the distribution network, the current filter output value is self-synchronized and adjusted to obtain a synchronized current filter output value. Based on the effective value of the zero-sequence voltage, the synchronized current filter output value data is preprocessed to obtain the grouped current value.

[0065] Step 3: Determine the Pearson correlation coefficient and the weighted Pearson correlation coefficient based on the grouped current values. Based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, determine whether the fault occurs within or outside the distribution network. Then, control the distribution network to perform protection actions according to the fault within or outside the distribution network.

[0066] Among them, determining the per-unit value of the effective value of the zero-sequence voltage of the distribution network node based on the instantaneous electrical quantity data includes:

[0067] Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes;

[0068] The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value.

[0069] Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

[0070] Specifically, a weighted first-order filtering method is used to filter the instantaneous electrical quantity data. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

[0071] Specifically, based on the fault time of the distribution network, the voltage filter output value and the current filter output value are self-synchronized and adjusted, including:

[0072] Determine the initial recording time;

[0073] If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array;

[0074] Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

[0075] The preprocessing of the synchronized current filter output value includes: performing average value calculation, grouping, summation calculation, and correction on the current filter output value in sequence.

[0076] Among them, the group current values ​​include: the node group current value below the mean and the node group current value above the mean.

[0077] The Pearson correlation coefficient and the weighted Pearson correlation coefficient are determined based on the grouped current values, including:

[0078] Based on the mean lower node group current value and the mean upper node group current value, generate an upper / lower node discrete signal sequence with corrected current sum;

[0079] The Pearson correlation coefficient and weighted Pearson correlation coefficient of the discrete signal sequence are determined according to a preset algorithm.

[0080] Among them, determining whether a fault occurs within or outside the distribution network area based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient includes:

[0081] If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate.

[0082] If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

[0083] The invention will be further described below with reference to specific implementations:

[0084] Implementation steps, such as Figure 2 As shown, it includes:

[0085] S1, using a data acquisition device to collect electrical quantities of each node in the power distribution network in real time;

[0086] S2, apply the weighted first-order filtering method to filter the electrical quantities of each node after sampling, and obtain the electrical quantities of each node after filtering;

[0087] S3, based on the time of the fault, performs self-synchronization adjustment of the electrical quantities of each node;

[0088] S4 transmits the effective value of zero-sequence voltage and the current filter output value of each node to the central control decision unit. After calculation, grouping, summation and correction, the current values ​​of "node grouping below the mean" and "node grouping above the mean" are obtained.

[0089] S5 calculates the Pearson correlation coefficient and the weighted Pearson correlation coefficient to determine whether the fault is inside or outside the zone, and realizes the rapid protection action of the self-synchronizing multi-terminal distribution network.

[0090] The following is a detailed explanation of S1-S5:

[0091] S1, using a data acquisition device to collect electrical quantities of each node in the power distribution network in real time;

[0092] Including the instantaneous values ​​of electrical quantities of each phase at the node Obtain the three-phase current array at any node i Three-phase voltage array Where i is the node number subscript, j is the electrical quantity subscript, including current electrical quantity I and voltage electrical quantity U, and p = a, b, c represent phase a, phase b, and phase c, respectively. Let K represent the phase value, and k represent the number of sampling points. In this invention, the total number of sampling points K = 2000, and the sampling frequency of the acquisition device is...

[0093] Based on the three-phase voltages obtained from the above sampling, calculate the zero-sequence voltage value at any node i.

[0094]

[0095] By applying the full-wave Fourier algorithm, the effective value of the zero-sequence voltage at any node i is obtained as x. i,U,abs And calculate the per-unit value x of the effective value of the zero-sequence voltage at any node i. i,U,abs * The calculation method is as follows:

[0096]

[0097] Among them, U B This represents the base voltage value, typically selected from the rated voltage U. N As the voltage base value.

[0098] When the per-unit value of the effective value of the zero-sequence voltage is x i,U,abs * Exceeding the threshold value Ks At that time, the protection criteria are activated:

[0099]

[0100] S2, apply the weighted first-order filtering method to filter the electrical quantities of each node after sampling, and obtain the electrical quantities of each node after filtering;

[0101] Among them, the weighted first-order filtering method is a software filtering algorithm, and the calculation process is as follows: Figure 3 As shown.

[0102] S2 specifically includes the following S21-S22:

[0103] S21, the instantaneous values ​​of electrical quantities at each node after each sampling. The weighted first-order filtering operation is performed as follows:

[0104]

[0105] in, This represents the filtered output value of the instantaneous electrical quantity at each node when the number of sampling points is k. This represents the sampled value of the instantaneous electrical quantity at each node when the number of sampling points is k. A represents the filtered output value of the instantaneous electrical quantity at each node when the number of sampling points is k-1; k The weighted filter coefficients for sampling point k satisfy the following constraints:

[0106]

[0107]

[0108]

[0109] In this invention:

[0110]

[0111] Specifically, the voltage filter output value at each node Current filter output value The calculation expression is:

[0112]

[0113]

[0114] Set the number of sampling points k = k + 1;

[0115] S22, Decision. Determine if the number of sampling points k = K = 2000. If the decision is true, end the above weighted first-order filtering process; if the decision is false, repeat S21.

[0116] S3, based on the time of the fault, performs self-synchronization adjustment of the electrical quantities of each node;

[0117] The fault timing is determined using a zero-crossing criterion based on positive and negative polarity. The calculation process of this method is as follows: Figure 4 As shown.

[0118] S3 specifically includes the following S31-S33:

[0119] S31, Set the initial recording time T ai =0, i=1,...,N, where N represents the number of nodes in the distribution network;

[0120] S32 performs zero-crossing detection on the voltage filter output value of each node:

[0121]

[0122] If the above criteria are met, node i is considered to have failed after the m-th sampling, and the zero-crossing time is set:

[0123]

[0124] Proceed to S33; if the above criteria are not met, it is assumed that node i has not experienced a fault after the mth sampling, the number of sampling points is set to m = m + 3, and S32 is repeated.

[0125] S33, perform self-synchronization adjustments on all nodes, including the following S331-S332.

[0126] S331, zero-crossing times T for all nodes ci Sort the arrays from smallest to largest to obtain the sorted array S:

[0127] [T c ] = [T c,1 ,T c,2 ,...,T c,N ]→S=[T d ] = [T d,1 ,T d,2 ,...,T d,N ] = [T c '] (11)

[0128] satisfy:

[0129] T d,1 <T d,2 <...<T d,N (12)

[0130] Among them, T d T represents the zero-crossing time of each node's fault after sorting.d,1 This represents the minimum zero-crossing time of each node.

[0131] S332, based on T d,1 Alignment adjustments are made to the measuring devices at all nodes at their initial moments.

[0132] T a,i =T c,i -T d,1 ,i=1,...,N (13)

[0133] Among them, T a,i This indicates the initial time of the data in each node after alignment adjustment. This allows for self-synchronization adjustment of all nodes.

[0134] S4 transmits the effective value of zero-sequence voltage and the current filter output value of each node to the central control decision unit. After calculation, grouping, summation and correction, the current values ​​of "node grouping below the mean" and "node grouping above the mean" are obtained.

[0135] S4 specifically includes the following S41-S43.

[0136] S41, transmit the effective value of the zero-sequence voltage and the current filter output value of each node to the central control decision unit, and based on the effective value of the zero-sequence voltage x of any node i calculated in S1. i,U,abs The current at each node is calculated and grouped, specifically including the following steps S411-S412.

[0137] S411, Calculate the average value of the effective value of the zero-sequence voltage of all nodes within the protection control zone.

[0138]

[0139] S412, grouping according to the effective value of zero-sequence voltage at each node:

[0140]

[0141]

[0142] Wherein, G1 and G2 represent “node grouping below the mean” and “node grouping above the mean”, respectively.

[0143] S42, within G1 and G2 respectively, filters the current output values ​​of each node in S2. Summing is performed to obtain the sum of the current filter output values ​​within G1 and G2.

[0144]

[0145]

[0146] S43, regarding the above Current correction:

[0147]

[0148]

[0149] in, The "corrected current sum" is referred to within G1 and G2; -0.5 < k1 < 0.5, -0.5 < k2 < 0.5. In this invention, k1 = 0.15, k2 = 0.12 are designed.

[0150] S5 calculates the Pearson correlation coefficient and the weighted Pearson correlation coefficient to determine whether the fault is within or outside the zone, enabling rapid protection actions in the self-synchronizing multi-terminal distribution network.

[0151] S5 specifically includes the following S51-S54.

[0152] S51 forms an array. Based on the "corrected current sum" within "node grouping below the mean" G1 and "node grouping above the mean" G2 in S4. Form a discrete signal sequence of "corrected current sum":

[0153]

[0154]

[0155] S52, calculate the Pearson correlation coefficient. For the discrete signal sequence [X] of the above "corrected current sum"... G1 ] and [X G2 ] Calculate its Pearson correlation coefficient cosα:

[0156]

[0157] In the formula: α represents a vector and The included angle of the inner product;

[0158]

[0159] K is the number of sampling points. In this invention, K = 2000.

[0160] In equation (23), -1 ≤ cosα ≤ 1 is satisfied: if and If perfectly positively correlated, then cosα = 1; if and If they are completely uncorrelated, then cosα = 0; if and If it is completely negatively correlated, then cosα = -1.

[0161] S53. Calculate the weighted Pearson correlation coefficient. Add the weight w to Equation (23) k to form the weighted Pearson correlation coefficient cosβ:

[0162]

[0163] where w k represents the weight of each sampling and satisfies the following constraint conditions:

[0164]

[0165]

[0166]

[0167] where H is a constant and satisfies 0.9 < H < 0.9. In the present invention, H = 0.75 is designed.

[0168] S54. Comprehensive judgment. According to the calculation results of Equation (23) and Equation (24):

[0169] If cosα > 0.9 and cosβ > 0.85, it is considered that and have strong correlation and high waveform similarity, then it is judged as an external fault and the protection does not operate; if cosα ≤ 0.9 or cosβ ≤ 0.85, it is considered that and have weak correlation and low waveform similarity, then it is judged as an internal fault and the protection operates.

[0170] A 10kV multi-terminal distribution network model as shown in Figure 5 is established on the PSCAD / EMTDC simulation platform. BUS1 - BUS2 represents the protection control area of the distribution network. Real-time information interaction is achieved through 5G network base stations and signal transmission.

[0171] The voltage level is 10kV, the line lengths are L1 = 25km, L2 = 30km, L3 = 30km, L4 = 35km, L5 = 33km, L6 = 30km, L7 = 18km, L8 = 21km; the line parameters are r1 = 0.021Ω / km, x1 = 0.2827Ω / km, r0 = 0.024Ω / km, x0 = 0.7194Ω / km, C0 = 0.005μF / km.

[0172] In the following simulation examples, the proposed scheme uses the following data:

[0173] The total number of sampling points K = 2000, the sampling frequency fs =20kHz; Rated voltage U N =10.5kV; Threshold value K s =0.3; Weighted filter coefficients:

[0174]

[0175] The total number of nodes N = 10; the correction coefficients k1 = 0.15, k2 = 0.12, and H = 0.75.

[0176] Scenario 1: A ground fault occurs in F1 within the zone:

[0177] Assuming that within a 100ms time window after startup, all data acquisition modules, weighted first-order filter modules, self-synchronization adjustment modules, and calculation-grouping-summing-correction modules are working normally, the central control decision unit can receive the zero-sequence voltage RMS value and current filter output value uploaded through the 5G network, and no data anomalies will occur.

[0178] A fault is set at point F1 (50km from busbar BUS1) within the zone, with a transition resistance of 0Ω and a phase-a ground fault. When a short-circuit fault occurs at point F1, various electrical quantities at each node of the distribution network can be collected in real time. Then, the per-unit value of the effective zero-sequence voltage at all nodes is calculated as follows:

[0179]

[0180] All protection criteria were activated normally.

[0181] Furthermore, a weighted first-order filtering algorithm can be applied to calculate the voltage output filter value and current output filter value for each sampling at each node. Taking the voltage output filter value with k=988 sampling points as an example, the calculation results are as follows:

[0182]

[0183] Furthermore, by applying the zero-crossing criterion based on positive and negative polarity, the zero-crossing times of each node can be calculated as follows:

[0184]

[0185] Zero-crossing time T for all nodes c,i Sort the arrays from smallest to largest to obtain the sorted array S:

[0186]

[0187] Therefore, based on T d，1 The alignment adjustment results for the initial moments of the measuring devices at all nodes are as follows:

[0188]

[0189] Furthermore, the average value of the effective zero-sequence voltage of all nodes within the protection control area is calculated. The result is: Therefore, “node grouping below the mean” G1 = {3, 4, 7, 8, 10}, and “node grouping above the mean” G2 = {1, 2, 5, 6, 9}.

[0190] Therefore, the sum of the current filter output values ​​within G1 and G2 can be calculated. And the corresponding "corrected current and".

[0191] Finally, based on the calculation formulas for Pearson correlation coefficient and weighted Pearson correlation coefficient, we can calculate that cosα = 0.645 < 0.9 and cosβ = 0.523 < 0.85. According to the protection scheme mentioned above, it can be determined that it is an intra-zone fault, and the protection device can correctly trip and clear the fault.

[0192] The waveform of the self-synchronization adjustment algorithm is as follows: Figure 6 As shown, under the condition of a phase-to-ground short-circuit fault at F1 and a transition resistance of 0Ω, the zero-sequence voltage amplitude waveform of the bus node after the fault is as follows: Figure 7 As shown, under the condition of a phase-to-ground short-circuit fault at F1 and a transition resistance of 0Ω, the zero-sequence current amplitude waveform of each line after the fault is as follows: Figure 8 As shown;

[0193] Scenario 2: A ground fault occurs at F2 in the area:

[0194] Similarly, assuming that within a 100ms time window after startup, all data acquisition modules, weighted first-order filter modules, self-synchronization adjustment modules, and calculation-grouping-summing-correction modules are working normally, the central control decision unit can receive the zero-sequence voltage RMS value and current filter output value uploaded through the 5G network, and no data anomalies will occur.

[0195] A fault is set at point F2 (15km from busbar BUS2) within the zone, with a transition resistance of 0Ω and a phase-to-ground short-circuit fault. When a short-circuit fault occurs at point F2, various electrical quantities at each node of the distribution network can be collected in real time. Then, the per-unit value of the effective zero-sequence voltage at all nodes is calculated as follows:

[0196]

[0197] All protection criteria were activated normally.

[0198] Furthermore, a weighted first-order filtering algorithm can be applied to calculate the voltage output filter value and current output filter value for each sampling at each node. Taking the voltage output filter value (k = 500 sampling points) as an example, the calculation results are as follows:

[0199]

[0200] Furthermore, applying the self-synchronization adjustment method based on the fault time, the alignment adjustment results for the initial times of the measuring devices at all nodes are as follows:

[0201]

[0202] Furthermore, the average value of the effective zero-sequence voltage of all nodes within the protection control area is calculated. The result is: Therefore, “node grouping below the mean” G1 = {4, 6, 7, 8}, and “node grouping above the mean” G2 = {1, 2, 3, 5, 9, 10}.

[0203] Therefore, the sum of the current filter output values ​​within G1 and G2 can be calculated. And the corresponding "corrected current and".

[0204] Finally, based on the calculation formulas for Pearson correlation coefficient and weighted Pearson correlation coefficient, we can calculate that cosα = 0.568 < 0.9 and cosβ = 0.613 < 0.85. According to the protection scheme mentioned above, it can be determined that the fault is within the zone, and the protection device can correctly trip and clear the fault.

[0205] Scenario 3: Grounding fault occurs in F3 outside the zone:

[0206] Similarly, assuming that within a 100ms time window after startup, all data acquisition modules, weighted first-order filter modules, self-synchronization adjustment modules, and calculation-grouping-summing-correction modules are working normally, the central control decision unit can receive the zero-sequence voltage RMS value and current filter output value uploaded through the 5G network, and no data anomalies will occur.

[0207] A fault is set at point F3 outside the distribution network (5km from busbar BUS2), with a transition resistance of 100Ω and a phase-c ground fault. When a short-circuit fault occurs at point F3, various electrical quantities at each node of the distribution network can be collected in real time. Then, the per-unit value of the effective zero-sequence voltage at all nodes is calculated as follows:

[0208]

[0209] All protection criteria were activated normally.

[0210] Furthermore, a weighted first-order filtering algorithm can be applied to calculate the voltage output filter value and current output filter value for each sampling at each node.

[0211] Furthermore, applying the self-synchronization adjustment method based on the fault time, the alignment adjustment results for the initial times of the measuring devices at all nodes are as follows:

[0212]

[0213] Furthermore, the average value of the effective zero-sequence voltage of all nodes within the protection control area is calculated. The result is: Therefore, the "node grouping below the mean" G1 = {6, 7, 8, 9, 10}, and the "node grouping above the mean" G2 = {1, 2, 3, 4, 5}.

[0214] Therefore, the sum of the current filter output values ​​within G1 and G2 can be calculated. And the corresponding "corrected current and".

[0215] Finally, based on the calculation formulas for Pearson correlation coefficient and weighted Pearson correlation coefficient, we can calculate that cosα = 0.928 > 0.9 and cosβ = 0.905 > 0.85. According to the protection scheme mentioned above, it can be determined that the fault is outside the zone, and the protection device will not operate.

[0216] Example 2:

[0217] The present invention also provides a self-synchronization protection system 200 for multi-terminal distribution networks, such as... Figure 9 As shown, it includes:

[0218] The acquisition unit 201 is used to acquire instantaneous electrical quantity data of each phase of the distribution network node at a preset acquisition frequency and number of sampling points, determine the per-unit value of the zero-sequence voltage effective value of the distribution network node based on the instantaneous electrical quantity data, and if the per-unit value of the zero-sequence voltage effective value is greater than a preset threshold, then the instantaneous electrical quantity data is filtered to obtain the current filtered output value and voltage filtered output value of the electrical quantity of the distribution network node.

[0219] The data processing unit 202 is used to perform self-synchronization adjustment on the current filter output value based on the fault time and voltage filter output value of the distribution network to obtain a synchronized current filter output value, and to preprocess the synchronized current filter output value data based on the zero-sequence voltage effective value to obtain grouped current values.

[0220] The control unit 203 is used to determine the Pearson correlation coefficient and the weighted Pearson correlation coefficient based on the grouped current values, determine whether a fault has occurred in or outside the distribution network based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, and control the distribution network to perform protection actions according to the fault in or outside the distribution network.

[0221] The acquisition unit 201 determines the per-unit value of the zero-sequence voltage RMS value of the distribution network node based on the instantaneous electrical quantity data, including:

[0222] Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes;

[0223] The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value.

[0224] Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

[0225] The acquisition unit 201 uses a weighted first-order filtering method to filter the instantaneous electrical quantity data. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

[0226] The data processing unit 202 performs self-synchronization adjustment of the voltage filter output value and the current filter output value based on the fault time of the distribution network, including:

[0227] Determine the initial recording time;

[0228] If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array;

[0229] Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

[0230] The data processing unit 202 preprocesses the synchronized current filter output value, including: performing average value calculation, grouping, summation calculation and correction on the current filter output value in sequence.

[0231] Among them, the group current values ​​include: the node group current value below the mean and the node group current value above the mean.

[0232] The control unit 203 determines the Pearson correlation coefficient and the weighted Pearson correlation coefficient based on the grouped current values, including:

[0233] Based on the mean lower node group current value and the mean upper node group current value, generate an upper / lower node discrete signal sequence with corrected current sum;

[0234] The Pearson correlation coefficient and weighted Pearson correlation coefficient of the discrete signal sequence are determined according to a preset algorithm.

[0235] The control unit 203 determines whether a fault occurs within or outside the distribution network area based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, including:

[0236] If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate.

[0237] If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

[0238] This invention utilizes the increasingly mature 5G communication technology to upload distribution network fault data within a specific area in real time. Based on this fault data, it achieves self-synchronization of multi-node sampling and comprehensively applies Pearson correlation coefficient and weighted Pearson correlation coefficient to compare the correlation of the composite currents on both sides of the line, ultimately achieving accurate identification of faults within and outside the area. This invention is expected to provide a low-latency, highly reliable, and rapid protection solution for urban multi-terminal distribution networks, thereby promoting the healthy development of urban distribution networks.

[0239] Example 3:

[0240] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, 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. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the methods in the above embodiments.

[0241] Example 4:

[0242] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiments.

[0243] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0244] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0245] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0246] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0247] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0248] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A self-synchronized protection method for a multi-terminal power distribution network, characterized in that, The method includes: The instantaneous electrical quantity data of each phase of the distribution network node are collected at a preset acquisition frequency and number of sampling points. Based on the instantaneous electrical quantity data, the per-unit value of the effective value of the zero-sequence voltage of the distribution network node is determined. If the per-unit value of the effective value of the zero-sequence voltage is greater than a preset threshold, the instantaneous electrical quantity data is filtered to obtain the current filtered output value and voltage filtered output value of the electrical quantity of the distribution network node. Based on the fault time and voltage filter output value of the distribution network, the current filter output value is self-synchronized and adjusted to obtain a synchronized current filter output value. Based on the effective value of the zero-sequence voltage, the synchronized current filter output value data is sequentially averaged, grouped, summed, and corrected. The average value calculation includes: calculating the average value of the effective value of the zero-sequence voltage of all nodes within the protection control area; The grouping process includes: grouping nodes based on the average value of the effective zero-sequence voltage of all nodes to obtain the node group below the mean and the node group above the mean; The summation calculation includes summing the current filter output values ​​of each node within the node grouping below the mean and the node grouping above the mean. The correction process includes: correcting the summation results of the current filtering output values ​​of each node in the lower mean node group and the upper mean node group to obtain the corrected current sum; Based on the corrected current and the generated discrete signal sequence, the Pearson correlation coefficient and weighted Pearson correlation coefficient of the discrete signal sequence are calculated. Based on the Pearson correlation coefficient and weighted Pearson correlation coefficient, it is determined whether the fault occurs in the distribution network within or outside the distribution network. Based on the fault in the distribution network within or outside the distribution network, the distribution network is controlled to perform protection actions. wherein the weighted Pearson correlation coefficient sample weight is calculated according to the following formula: where K is the number of sampling points, k is the sampling node, H = 0.

75.

2. The method according to claim 1, characterized in that, The step of determining the per-unit value of the zero-sequence voltage RMS value of the distribution network node based on the instantaneous electrical quantity data includes: Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes; The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value. Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

3. The method of claim 1, wherein, The instantaneous electrical quantity data is filtered using a weighted first-order filtering method. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

4. The method of claim 1, wherein, The self-synchronization adjustment of the voltage filter output value and current filter output value based on the fault time of the distribution network includes: Determine the initial recording time; If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array; Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

5. The method of claim 1, wherein, The determination of whether a fault occurs within or outside the distribution network based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient includes: If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate. If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

6. A self-synchronized protection system for a multi-terminal electric power distribution network, characterized in that, The system includes: The acquisition unit is used to acquire instantaneous electrical quantity data of each phase of the distribution network node at a preset acquisition frequency and number of sampling points. Based on the instantaneous electrical quantity data, the per-unit value of the effective value of the zero-sequence voltage of the distribution network node is determined. If the per-unit value of the effective value of the zero-sequence voltage is greater than a preset threshold, the instantaneous electrical quantity data is filtered to obtain the current filtered output value and voltage filtered output value of the electrical quantity of the distribution network node. The data processing unit is used to perform self-synchronization adjustment on the current filter output value based on the fault time and voltage filter output value of the distribution network to obtain a synchronized current filter output value, and to perform average calculation, grouping, summation calculation and correction processing on the synchronized current filter output value data based on the zero-sequence voltage effective value. The average value calculation includes: calculating the average value of the effective value of the zero-sequence voltage of all nodes within the protection control area; The grouping process includes: grouping nodes based on the average value of the effective zero-sequence voltage of all nodes to obtain the node group below the mean and the node group above the mean; The summation calculation includes summing the current filter output values ​​of each node within the node grouping below the mean and the node grouping above the mean. The correction process includes: correcting the summation results of the current filtering output values ​​of each node in the lower mean node group and the upper mean node group to obtain the corrected current sum; The control unit is used to generate a discrete signal sequence based on the corrected current, calculate the Pearson correlation coefficient and the weighted Pearson correlation coefficient of the discrete signal sequence, determine whether a fault occurs in or outside the distribution network based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, and control the distribution network to perform protection actions according to the fault in or outside the distribution network. wherein the weighted Pearson correlation coefficient sample weight is calculated according to the following formula: where K is the number of sampling points, k is the sampling node, H = 0.

75.

7. The system of claim 6, wherein, The acquisition unit determines the per-unit value of the zero-sequence voltage RMS value of the distribution network node based on the instantaneous electrical quantity data, including: Based on the instantaneous electrical quantity data, determine the three-phase voltage array of the distribution network nodes; The zero-sequence voltage value of the distribution network node is determined based on the three-phase voltage array, and the effective value of the zero-sequence voltage of the distribution network node is determined based on the zero-sequence voltage value. Based on the effective value of the zero-sequence voltage of the distribution network node, determine the per-unit value of the effective value of the zero-sequence voltage of the distribution network node.

8. The system of claim 6, wherein, The acquisition unit uses a weighted first-order filtering method to filter the instantaneous electrical quantity data. When the number of sampling points is determined to be a preset value, the filtering of the instantaneous electrical quantity data is terminated.

9. The system according to claim 6, characterized in that, The data processing unit performs self-synchronization adjustment of the voltage filter output value and the current filter output value based on the fault time of the distribution network, including: Determine the initial recording time; If the voltage filter output value satisfies the zero-crossing criterion, the zero-crossing times of the distribution network nodes are sorted to obtain a sorted array; Based on the recorded initial time and sorted array, the initial times of the voltage filter output value and the current filter output value are aligned and adjusted.

10. The system of claim 6, wherein, The control unit determines whether a fault occurs within or outside the distribution network area based on the Pearson correlation coefficient and the weighted Pearson correlation coefficient, including: If the Pearson correlation coefficient is greater than 0.9 and the weighted Pearson correlation coefficient is greater than 0.85, then it is determined that an external fault has occurred in the distribution network, and the distribution network protection is controlled not to operate. If the Pearson correlation coefficient is not greater than 0.9 or the weighted Pearson correlation coefficient is not greater than 0.85, then a fault is determined to occur within the distribution network area, and the distribution network protection is controlled to operate.

11. A computer device, characterized by include: One or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described in any one of claims 1-5 is implemented.

12. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method as described in any one of claims 1-5.

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