KR102225625B1 - Real-time power system fault location estimation system and method - Google Patents

Abstract

The present invention provides a real-time power system fault location estimation system, which comprises: a reference fault propagation information measurement unit for measuring reference fault propagation information flowing from a phasor measurement unit (PMU) of a plurality of buses constituting a power system to a transmission line connecting the buses; an initial fault propagation information measurement unit for measuring initial fault propagation information based on past fault data information previously stored in a network connected to the power system; and a main fault location estimation unit for estimating the fault location in the transmission line in real time by comparing the reference fault propagation information measured from the reference fault propagation information measurement unit and the correlation coefficient corresponding to the initial fault propagation information measured from the initial fault propagation information measurement unit. It has the effect of implementing a fault location estimation technique without directly measuring the propagation speed and time of a disturbance signal.

Description

Real-time power system fault location estimation system and method based on fault signal propagation time

The present invention relates to the estimation of the fault location of the power system, and more particularly, to estimate the fault location in the power system in real time by measuring and analyzing the propagation time of the fault signal, real-time power system fault location estimation based on the fault signal propagation time It relates to systems and methods.

In general, a technique for estimating the location of various fault phenomena occurring in the power system in real time has been studied theoretically. For example, it is a method of estimating the location of occurrence by analyzing the propagation speed of a fault signal through the form of an electromechanical wave and measuring the arrival time at each measurement location.

However, in the actual power system, 1) it is impossible to implement a measurement system with a high resolution that allows the propagation time measurement in the power system, 2) there is uncertainty in the state variables of the power system that determine the propagation speed, and 3) constantly changing. Due to the presence of the power system topology, it is difficult to directly use the analysis results of the fault signal propagation phenomena for direct fault location estimation.

In addition, failure of the power system can occur anywhere in the system. In this case, when a failure occurs, it appears as a disturbance in the voltage and frequency signals. This disturbance signal is propagated throughout the power system through the transmission line, and the disturbance can be recognized through the PMU. The propagation speed of disturbance is determined by variables such as inertia and line impedance of the power system according to the electromechanical wave theory, but there is a limitation in calculating the accurate speed because the exact value of the variable and the model structure are not known in the actual power system.

Accordingly, there is a need to develop a more reliable fault location estimation technique through a learning process that considers various variables without directly measuring the propagation speed and time of the disturbance signal in the power system.

U.S. Patent Publication No. 9746511

Accordingly, the present invention has been proposed in consideration of the above matters, and an object of the present invention is to implement a technique for estimating a fault location without direct measurement of the propagation speed and time of a disturbance signal.

In addition, it is an object of the present invention to set the propagation time required by each transmission line as a weight value, and to enable efficient fault location estimation by constructing a fault occurrence model structure based on this.

In addition, an object of the present invention is to implement a fault location estimation technique in consideration of continuously changing power system change factors by using information of past fault data stored and updated in a network connected to the power system.

In addition, an object of the present invention is to enable stepwise estimation by using a binary search method optimized for estimating a fault location in a transmission line.

In addition, an object of the present invention is to consider the variability of the fault location estimation by calculating a trend signal from a measurement signal having high variability by using the slope value of the accumulated signal in the analysis of the synchronization phase measurement signal.

In addition, the present invention deduces the shortest path in the power system and distinguishes whether the value of the propagation time obtained through comparison between the measurement stations of each synchronization phase corresponds to the propagation time of the faulty signal or the difference between the propagation time reached through other paths. Therefore, it aims to increase the reliability of the fault location estimation.

In addition, the present invention is to increase the reliability of fault location estimation by obtaining a pattern in which the weight values of each transmission line are combined, calculating a correlation coefficient value between each pattern, determining the similarity, and obtaining the most suitable pattern location. The purpose.

The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, the real-time power system fault location estimation system based on the fault signal propagation time according to the technical idea of the present invention is a synchronous phase device (PMU) of a plurality of electrical buses constituting the power system. unit) to the transmission line that connects the buses, the standard fault propagation information measuring unit that measures the standard fault propagation information, which measures the initial fault propagation information based on the past fault data information previously stored in the network connected to the power system. Failure in the transmission line by comparing the correlation coefficient corresponding to the fault propagation information measuring unit, the reference fault propagation information measured from the reference fault propagation information measuring unit and the initial fault propagation information measured by the initial fault propagation information measuring unit It may include a main fault location estimation unit for estimating the location in real time.

In this case, the reference fault propagation information measuring unit is a frequency signal measuring unit that measures a frequency signal from each synchronization phase of a plurality of buses constituting a power system, and a difference signal of each sampling corresponding to before and after a predetermined period of the measured frequency signal. An accumulated signal calculation unit that generates and calculates an accumulated signal for each synchronization phase based on this, a slope value calculation unit that linearizes the calculated accumulated signal to calculate a slope value for each synchronization phase, and the calculated slope for each synchronization phase It may include a reference fault propagation information defining unit defining a difference value between the values as a reference weight value corresponding to a difference between the reference fault propagation times flowing through each transmission line.

The cumulative signal calculator may calculate the cumulative signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the cumulative signal calculation equation represented by Equation 1 below.

<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant)

The slope value calculator may calculate a slope value for each synchronization phase by linearizing the calculated accumulated signal according to the slope value calculation equation expressed by Equation 2 below.

<Equation 2>

: 기울기 값, t: 시간(초), Nw: 시간윈도우 내의 샘플 개수, k: 임의변수, i: i번째 동기위상기)(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase)

The initial failure propagation information measuring unit is an initial weight value defining unit that defines an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line, and is preset based on the defined initial weight value. A shortest path derivation unit that derives the shortest path from the fault location to each bus of the power system, and a transmission line division unit that divides at least one transmission line existing on the derived shortest path from each of the previously stored transmission lines , After correcting each initial weight value corresponding to the at least one divided transmission line based on a neural network learning algorithm taking into account the derived shortest path, including an initial failure propagation information definition unit defining this as initial failure propagation information. can do.

The shortest path derivation unit may derive at least one or more shortest paths from the preset fault location to the bus of the power system using a Dijkstra algorithm.

The main fault location estimation unit calculates a fault bus in which a correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit and the initial fault propagation information measured by the initial fault propagation information measuring unit is maximum. A faulty bus calculation unit may include a sub fault location estimating unit for estimating a fault location in the transmission line in real time by performing a binary search on a transmission line connecting the calculated faulty bus.

The fault bus calculation unit is a correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit based on Equations 3 and 4 below, and the initial fault propagation information measured by the initial fault propagation information measuring unit. It is possible to calculate the faulty bus where is the maximum.

<Equation 3>

: 가중치벡터 평균값, mi: i번째 측정 기울기값,

: 측정벡터 평균값)(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)

<Equation 4>

,

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position)

The sub-failure location estimating unit may estimate the location of the failure in the transmission line in real time based on Equation 5 below.

<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches)

On the other hand, in order to achieve the above object, the real-time power system fault location estimation system based on the fault signal propagation time according to the technical idea of the present invention connects the reference weight value defined by the reference fault propagation information definition unit to the power system. It may further include an update unit for updating past fault data information by storing it in the network.

In order to achieve the above object, the real-time power system fault location estimation method based on the fault signal propagation time according to the technical idea of the present invention is the synchronization of a plurality of electric buses constituting the power system in the reference fault propagation information measuring unit. The reference fault propagation information measurement step of measuring the reference fault propagation information flowing from the phaser (Phasor measurement unit) to the transmission line connecting the buses, the past previously stored in the network connected to the power system by the initial fault propagation information measuring unit From the initial fault propagation information measuring step of measuring initial fault propagation information based on fault data information, the reference fault propagation information measured from the reference fault propagation information measuring step in the main fault location estimation unit, and the initial fault propagation information measuring step. It may include a main fault location estimating step of estimating a fault location in the transmission line in real time by comparing a correlation coefficient corresponding to the measured initial failure propagation information.

In this case, the reference fault radio wave information measuring step is a frequency signal measuring step of measuring a frequency signal from each synchronization phase of a plurality of buses constituting a power system in the frequency signal measuring unit, and the measured frequency signal in the accumulated signal calculating unit. An accumulated signal calculation step of generating a difference signal for each sampling corresponding to before and after a predetermined period of time and calculating an accumulated signal for each synchronization phase based on this, and a slope value for each synchronization phase by linearizing the calculated accumulated signal in a slope value calculator A reference fault in which the difference between the slope values calculated by the reference fault propagation information definition unit for calculating the slope value of the reference fault propagation information definition unit is defined as a reference weight value corresponding to the difference between the reference fault propagation times flowing through each transmission line. It may include the step of defining radio information.

The cumulative signal calculation step may calculate the cumulative signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the cumulative signal calculation equation represented by Equation 1 below.

<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant)

In the slope value calculation step, a slope value for each synchronization phase may be calculated by linearizing the calculated cumulative signal according to the slope value calculation equation represented by Equation 2 below.

<Equation 2>

: 기울기 값, t: 시간(초), Nw: 시간윈도우 내의 샘플 개수, k: 임의변수, i: i번째 동기위상기)(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase)

The initial failure propagation information measurement step is an initial weight value definition step of defining an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line in the initial weight value definition unit, and a shortest path derivation unit In the shortest path derivation step of deriving the shortest path from the preset fault location to each bus of the power system based on the defined initial weight value, at least one existing on the shortest path derived from the transmission line division unit A transmission line classification step of dividing the above transmission lines from each of the previously stored transmission lines, and a neural network in which each initial weight value corresponding to the at least one divided transmission line is determined by the faulty propagation information definition unit in consideration of the derived shortest path After correcting based on the learning algorithm, it may include an initial failure propagation information definition step of defining it as initial failure propagation information.

In the step of deriving the shortest path, at least one or more shortest paths from the preset fault location to the bus of the power system may be derived using a Dijkstra algorithm.

In the main fault location estimation step, the correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring step in the fault bus calculation unit and the initial fault propagation information measured from the initial fault propagation information measuring step is the maximum. A faulty bus calculation step of calculating a faulty bus that is a faulty bus, a sub fault location in which the fault location in the transmission line is estimated in real time by binary search of the transmission line connecting the faulty bus by the sub fault location estimation unit It may include an estimation step.

The failure bus calculation step is based on Equations 3 and 4 below, corresponding to the reference failure propagation information measured from the reference failure propagation information measuring unit, and the initial failure propagation information measured by the initial failure propagation information measuring unit. The faulty bus with the maximum correlation coefficient can be calculated.

<Equation 3>

: 가중치벡터 평균값, mi: i번째 측정 기울기값,

: 측정벡터 평균값)(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)

<Equation 4>

,

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position)

In the sub-failure location estimation step, a failure location in the transmission line may be estimated in real time based on Equation 5 below.

<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches)

Meanwhile, the network connected to the power system may be referred to as a network in which past fault data information is updated by storing a reference weight value defined in the step of defining the reference fault propagation information by an update unit.

According to the real-time power system fault location estimation system and method based on the fault signal propagation time as described above,

First, it has the effect of implementing a fault location estimation technique without direct measurement of the propagation speed and time of the disturbance signal.

Second, the propagation time required by each transmission line is set as a weight value, and an efficient fault location estimation is possible by constructing a fault occurrence model structure based on this.

Third, by using the information of past fault data stored and updated in the network connected to the power system, it has the effect of implementing a fault location estimation technique in consideration of continuously changing power system change factors.

Fourth, it has the effect of enabling stepwise estimation by using a binary search method optimized for estimating a fault location in a transmission line.

Fifth, in the analysis of the synchronization phase measurement signal, the trend signal is calculated from the measurement signal having high variability using the slope value of the accumulated signal, thereby having the effect of taking into account the variability of the fault location estimation.

Sixth, by deriving the shortest path in the power system and determining whether the value of the propagation time obtained through comparison between the measurement stations of each synchronization phase corresponds to the propagation time of the fault signal or the difference between the propagation time reached through another path, the fault location It has the effect of increasing the reliability of estimation.

Seventh, the effect of increasing the reliability of the fault location estimation is obtained by obtaining a pattern in the form of a combination of the weight values of each transmission line, calculating the correlation coefficient between each pattern, determining the similarity, and obtaining the most suitable pattern location. Have.

1 is a block diagram showing a real-time power system fault location estimation system based on a fault signal propagation time according to an embodiment of the present invention.
2 is a diagram showing a case in which a fault signal propagates in a power system as an embodiment of the present invention.
FIG. 3 is a diagram showing measurement results of two different fault condition frequency signals through four synchronization phase machines (PMUs) as an embodiment of the present invention.
4 is a view showing a result of calculating an accumulated signal based on the frequency signal measurement result according to FIG. 3.
FIG. 5 is a diagram illustrating a ratio between a linear approximation value of a rate of change of frequency (ROCOF) and a threshold value based on a result of calculating the accumulated signal according to FIG. 4.
6 is a diagram showing a result of dividing a transmission line existing on a shortest path as an embodiment of the present invention.
7 is a diagram illustrating a process of estimating a fault location through binary search as an embodiment of the present invention.
8 is a flowchart illustrating a method of estimating a real-time power system fault location based on a fault signal propagation time according to an embodiment of the present invention.
9 is a flow chart showing a reference fault propagation information measuring step (S100) according to FIG.
10 is a flow chart showing the initial failure propagation information measuring step (S200) according to FIG.
11 is a flow chart showing a main fault location estimation step (S300) according to FIG.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the implementation of the present invention, reference should be made to the accompanying drawings illustrating preferred embodiments of the present invention and the contents described in the accompanying drawings. Features and advantages of the present invention will become more apparent from the following detailed description based on the accompanying drawings. Prior to this, terms or words used in the present specification and claims are based on the principle that the inventor can appropriately define the concept of the term in order to explain it in the best way of his own invention. It should be interpreted as a corresponding meaning and concept. In addition, when it is determined that the detailed description of known functions and configurations thereof related to the present invention may unnecessarily obscure the subject matter of the present invention, it should be noted that the detailed description thereof has been omitted.

The broadband power system can be analyzed as a network of transmission lines connecting the buses with an electrical bus. At this time, the PMU (Phasor measurement unit) can be said to be a device that measures voltage, current, and frequency signals in the form of a phase synchronized through GPS at a sampling frequency of 30 to 60 Hz on each bus.

The present invention will be described based on this concept as follows.

1 is a block diagram showing a system for estimating a real-time power system fault location based on a fault signal propagation time according to an embodiment of the present invention.

1, the real-time power system fault location estimation system based on a fault signal propagation time according to an embodiment of the present invention is largely a reference fault propagation information measuring unit 100, an initial fault propagation information measuring unit 200, and a main fault. It may include a location estimation unit 300.

The reference fault propagation information measuring unit 100 measures the reference fault propagation information flowing from a Phasor measurement unit (PMU) of a plurality of electrical buses constituting a power system to a transmission line connecting buses. I can.

In more detail, the reference fault propagation information measuring unit 100 includes a frequency signal measuring unit 110, an accumulated signal calculating unit 130, a slope value calculating unit 150, and a reference fault propagation information defining unit 170. I can.

The frequency signal measurement unit 110 may measure a frequency signal from each synchronization phase of a plurality of buses constituting a power system. This is a component for indirectly measuring the disturbance signal propagating through the transmission line through the PMU, without directly measuring the disturbance signal (failure signal).

An embodiment of the frequency signal measuring unit 110 may be described with reference to FIGS. 2 and 3.

2 is a diagram showing a case in which a fault signal is propagated in the power system as an embodiment of the present invention, and FIG. 3 is an embodiment of the present invention, two different faults through four synchronous phase units (PMUs). It is a diagram showing the result of measuring the situation frequency signal. At this time, FIG. 3(a) is a frequency signal of a first event (failure situation), and FIG. 3(b) is a frequency signal of a second event (failure situation).

As shown in Fig. 2, a fault signal (Event) occurring in the power system can be propagated through all transmission lines (wij: weight of the line between bus bi and bj, tij: between bus bi and bj. Time difference), in this case, the frequency signal measuring unit 110 may be referred to as a component for measuring a frequency signal by using this characteristic.

In addition, a result of measuring a frequency signal from each synchronization phase through the frequency signal measuring unit 100 is shown in FIG. 3.

The accumulated signal calculation unit 130 may generate a difference signal for each sampling corresponding to before and after a predetermined period of the frequency signal measured by the frequency signal measurement unit 110 and calculate the accumulated signal for each synchronization phase based on the generated difference signal. This can be said to be a component to consider the variability of the fault location estimation by calculating the trend signal from the highly volatile measurement signal.

At this time, the cumulative signal calculation unit 130 calculates the cumulative signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the cumulative signal calculation equation represented by Equation 1 below. Can be calculated.

<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant)

An embodiment of the accumulated signal calculating unit 130 may be described with reference to FIG. 4.

4 is a diagram showing a result of calculating an accumulated signal based on the frequency signal measurement result according to FIG. 3.

As shown in FIG. 4, the frequency signal measured by the frequency signal measuring unit 110 may be calculated as an accumulated signal, that is, an accumulated signal through generation of a difference signal. 4 may be regarded as a result of accumulating the difference value as an absolute value.

The slope value calculation unit 150 may linearize the cumulative signal calculated by the cumulative signal calculation unit 130 to calculate a slope value for each synchronization phase.

In this case, the slope value calculator 150 may linearize the calculated accumulated signal according to the slope value calculation equation expressed by Equation 2 below to calculate a slope value for each synchronization phase.

<Equation 2>

: 기울기 값, t: 시간(초), Nw: 시간윈도우 내의 샘플 개수, k: 임의변수, i: i번째 동기위상기)(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase)

The reference fault propagation information defining unit 170 may define the reference fault propagation information based on a slope value for each synchronization phase calculated from the slope value calculating unit 150. In more detail, the reference fault propagation information definition unit 170 defines the difference value between the slope values for each synchronization phase as a ratio corresponding to the difference between the reference fault propagation times flowing through each transmission line, that is, a reference weight value. The reference weight value defined here may be referred to as the reference failure propagation information. This can be said to be a component for setting the propagation time required by each transmission line as a weight value in order to establish a failure occurrence model structure.

An embodiment of the slope value calculation unit 150 and the reference fault propagation information definition unit 170 may be described with reference to FIG. 5.

FIG. 5 is a diagram illustrating a ratio between a linear approximation value of a rate of change of frequency (ROCOF) and a threshold value based on a result of calculating the accumulated signal according to FIG. 4.

As shown in FIG. 5, the accumulated signal calculated from the accumulated signal calculating unit 130 is linearized to calculate a slope value for each synchronization phase, and a difference value between the slope values for each synchronization phase is a reference fault flowing through each transmission line. It may be defined as a ratio corresponding to the difference between propagation times, that is, a reference weight value. In this case, since the ratio of the reference weight values is the same regardless of the threshold value, it is not necessary to set the threshold value.

Meanwhile, the real-time power system fault location estimation system based on the fault signal propagation time according to an embodiment of the present invention may further include an update unit (not shown).

The update unit may update past failure data information by storing a reference weight value defined by the reference failure propagation information definition unit 170 in a network connected to the power system. This can be said to be a component to consider continuously changing power system change factors by using information of past fault data stored and updated in a network connected to the power system.

The initial failure propagation information measuring unit 200 may measure initial failure propagation information based on past failure data information previously stored in a network connected to the power system.

In more detail, the initial failure propagation information measuring unit 200 includes an initial weight value defining unit 210, a shortest path deriving unit 230, a transmission line classifying unit 250, and an initial failure propagation information defining unit 270. can do.

The initial weight value defining unit 210 may define an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line. This can be said to be a component for normalizing the initial weight values of each of the previously stored transmission lines.

The shortest path derivation unit 230 may derive a shortest path from a preset fault location to each bus of the power system based on an initial weight value defined by the initial weight value definition unit 210. It derives the shortest path in the power system and estimates the location of the fault by distinguishing whether the value of the propagation time obtained through comparison between the measurement stations of each synchronized phase corresponds to the propagation time of the fault signal or the difference between the propagation time reached through other paths. It can be said to be a component to increase the reliability of the product. At this time, the preset fault location can be referred to as a randomly preset fault location.

On the other hand, the shortest path from an arbitrary preset fault location to the bus of the power system can be said to derive all the shortest paths for each bus and obtain all combinations of the shortest paths in the power system that can be calculated from the set fault location.

In this case, the shortest path derivation unit 230 may derive at least one shortest path from the preset fault location to the bus of the power system using a Dijkstra algorithm. At this time, the Dijkstra algorithm can be said to be an appropriate algorithm to calculate the shortest path between each synchronization phase through the weight value and connection information when the shortest path is derived.

The transmission line classifying unit 250 may classify at least one transmission line existing on the shortest path derived from the shortest path deriving unit 230 from each transmission line previously stored in a network connected to the power system. The reason is that the weight of the time difference measured at both ends of the transmission line existing on the shortest path corresponds to the ratio of the time taken for the fault signal to propagate, but the time difference measured at both ends of the transmission line that does not exist on the shortest path This is because the weight of is not in accordance with the time difference of the corresponding transmission line due to the time difference of the radio signal arriving through another path.

An embodiment of the transmission line classification unit 250 may be described with reference to FIG. 6.

6 is a diagram showing a result of dividing a transmission line existing on a shortest path as an embodiment of the present invention. FIG. 6(a) is a combination of weight values of transmission lines on the shortest path, and FIG. 6(b) is a corresponding value of time differences measured in the same transmission lines. At this time, the line number corresponding to the x-axis is a value obtained by assigning a number to each transmission line, and the y-axis is the direction of propagation of fault signals.

For example, if a value obtained by subtracting a signal value of a bus with a small number from a signal value of a bus with a large number is a positive value, it can be said that a fault signal propagates from a bus with a large number to a bus with a small number. Conversely, if the value obtained by subtracting the signal value of the small numbered bus from the signal value of the large numbered bus is a negative value, it can be said that the fault signal propagates from the small numbered bus to the large numbered bus.

Referring to FIG. 6, a transmission line having a propagation direction of 0 such as x-axis values 20 and 40 may be regarded as a transmission line without a derived shortest path.

The initial failure propagation information defining unit 270 may define initial failure propagation information based on each initial weight value corresponding to at least one transmission line divided from the transmission line classifying unit 250. In more detail, the initial failure propagation information defining unit 270 may correct each initial weight value corresponding to the divided at least one transmission line, and then define the corrected weight value as initial failure propagation information. This can be said to be a component for utilizing past fault data information previously stored in the network connected to the power system.

At this time, each initial weight value correction may be corrected in consideration of the shortest path derived from the shortest path derivation unit 230. And correction can use a neural network learning algorithm.

An example of correcting each initial weight value using a neural network learning algorithm is shown in Table 1 below.

<Table 1>

은 최단경로 보정을 위한 가중치값 업데이트 보정상수,

은 동일 최단경로에서 가중치값 업데이트를 위한 보정상수라 할 수 있다.Table 1 is an example of a neural network learning algorithm according to an embodiment of the present invention. Referring to Table 1, W may be a weight matrix, and M may be a measurement matrix measured from a synchrophasor. (#event) is the number of failure cases of all data, (#lines) is the number of transmission lines in the power system, and shortest paths are the shortest paths,

Is the weight value update correction constant for the shortest path correction,

May be referred to as a correction constant for updating the weight value in the same shortest path.

In this case, W corresponds to the initial weight value, and W'may be referred to as a corrected initial weight value.

Referring to Table 1, the initial weight value may be adjusted in detail while adjusting the shortest path based on the algorithm.

The main fault location estimation unit 300 is a correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit 100 and the initial fault propagation information measured by the initial fault propagation information measuring unit 200 Through comparison, it is possible to estimate the location of a failure in the transmission line constituting the power system in real time.

In more detail, the main failure location estimation unit 300 may include a failure bus calculation unit 310 and a sub failure location estimation unit 330.

The fault bus calculation unit 310 has a correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit 100 and the initial fault propagation information measured by the initial fault propagation information measuring unit 200 The maximum faulty bus can be calculated. This is a component to increase the reliability of fault location estimation by obtaining a pattern in the form of a combination of the weight values of each transmission line, calculating the correlation coefficient between each pattern, determining the similarity, and obtaining the most suitable pattern location. I can.

At this time, the fault bus calculation unit 310 includes the reference fault propagation information measured from the reference fault propagation information measuring unit 100 based on Equations 3 and 4 below, and the initial fault propagation information measuring unit 200 It is possible to calculate the fault bus with the maximum correlation coefficient corresponding to the initial fault propagation information measured from.

<Equation 3>

: 가중치벡터 평균값, mi: i번째 측정 기울기값,

: 측정벡터 평균값)(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)

<Equation 4>

,

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position)

The sub-fault location estimating unit 330 may binary search the transmission line connecting the faulty bus calculated by the faulty bus calculation unit 310 to estimate the fault location in the transmission line in real time. This can be said to be a component for implementing a step-by-step fault location estimation function using a binary search method optimized for fault location estimation in a transmission line.

In this case, the sub-failure location estimating unit 330 may estimate the location of the failure in the transmission line in real time based on Equation 5 below. This is the same as in FIG. 5.

<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches)

An embodiment of the sub-failure location estimating unit 330 may be described with reference to FIG. 7.

7 is a diagram illustrating a process of estimating a fault location through binary search as an embodiment of the present invention.

As shown in FIG. 7, in the estimation of a fault location, a line can be divided into two sections step by step, and the correlation coefficients of the center positions of the two sections can be compared. In addition, each time the correlation coefficient is compared, it is possible to perform step-by-step failure location estimation by narrowing down to one section.

At this time, the binary search is performed up to four basic steps, and the number of searches can be easily changed, such as performing additional calculations according to the calculation speed.

8 is a flowchart illustrating a method of estimating a fault location in a real-time power system based on a fault signal propagation time according to an embodiment of the present invention.

Referring to FIG. 8, a method for estimating a real-time power system fault location based on a fault signal propagation time according to an embodiment of the present invention includes a reference fault propagation information measuring step (S100), an initial fault propagation information measuring step (S200) and a main fault It may include a position estimation step (S300).

The reference fault propagation information measurement step is performed by the reference fault propagation information measuring unit 100 from the Phasor measurement unit (PMU) of a plurality of electrical buses constituting the power system to a transmission line connecting the buses. Reference failure propagation information can be measured (S100).

In more detail, the reference failure propagation information measuring step (S100) may be described with reference to FIG. 9.

9 is a flow chart showing a reference fault propagation information measuring step (S100) according to FIG.

As shown in Fig. 9, the reference fault propagation information measuring step (S100) includes a frequency signal measuring step (S110), an accumulated signal calculating step (S130), a slope value calculating step (S150), and a reference fault propagation information defining step (S170). ) Can be included.

In the frequency signal measurement step, the frequency signal measurement unit 110 may measure a frequency signal from each synchronization phase of a plurality of buses constituting the power system (S110). This is a step for indirectly measuring the disturbance signal propagating through the transmission line through the PMU, without directly measuring the disturbance signal (failure signal).

In the cumulative signal calculation step, the cumulative signal calculation unit 130 generates a difference signal for each sampling corresponding to before and after a predetermined period of the frequency signal measured in the frequency signal measuring step (S110), and based on this, the cumulative signal for each synchronization phase is generated. It can be calculated (S130). This can be said to be a step to consider the variability of the fault location estimation by calculating the trend signal from the highly volatile measurement signal.

In this case, the accumulated signal calculation step (S130) calculates the accumulated signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the accumulated signal calculation equation expressed by Equation 1 below. Can be calculated.

<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant)

In the slope value calculation step, the slope value calculation unit 150 linearizes the cumulative signal calculated from the cumulative signal calculation step S130 to calculate a slope value for each synchronization phase (S150).

In this case, the slope value calculation step S150 may linearize the calculated accumulated signal according to the slope value calculation equation expressed by Equation 2 below to calculate a slope value for each synchronization phase.

<Equation 2>

: 기울기 값, t: 시간(초), Nw: 시간윈도우 내의 샘플 개수, k: 임의변수, i: i번째 동기위상기)(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase)

In the step of defining the reference fault propagation information, the reference fault propagation information may be defined based on the slope value for each synchronization phase calculated from the slope value calculation step S150 in the reference fault propagation information definition unit 170 (S170 ). In more detail, the reference fault propagation information definition step (S170) is defined as a ratio corresponding to the difference between the reference fault propagation times flowing through each transmission line, that is, a reference weight value, for the difference value between the slope values for each synchronization phase. The reference weight value defined here may be referred to as the reference failure propagation information. This can be said to be a step for setting the propagation time required by each transmission line as a weight value in order to establish a failure occurrence model structure.

In this case, the construction of the failure occurrence model structure can be said to be a network connected to the power system. The power system network may be referred to as a network in which past failure data information is updated by storing a reference weight value defined in the reference failure propagation information definition step S170 by an update unit (not shown). This can be said to be a feature to consider continuously changing power system change factors by using information of past fault data stored and updated in a network connected to the power system.

In the initial failure propagation information measuring step, the initial failure propagation information measurement unit 200 may measure the initial failure propagation information based on past failure data information previously stored in the network connected to the power system (S200).

In more detail, the initial failure propagation information measuring step (S200) may be described with reference to FIG. 10.

10 is a flow chart showing the initial failure propagation information measurement step (S200) according to FIG.

10, the initial failure propagation information measurement step (S200) includes an initial weight value definition step (S210), a shortest path derivation step (S230), a transmission line classification step (S250), and an initial failure propagation information definition step ( S270) may be included.

In the initial weight value defining step, the initial weight value defining unit 210 may define an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line (S210). This can be said to be a step for normalizing the initial weight value of each transmission line that has been previously stored.

In the shortest path derivation step, the shortest path to each bus of the power system can be derived from a preset fault location based on the initial weight value defined in the initial weight value definition step (S210) in the shortest path derivation unit 230. Yes (S230). It derives the shortest path in the power system and estimates the location of the fault by distinguishing whether the value of the propagation time obtained through comparison between the measurement stations of each synchronized phase corresponds to the propagation time of the fault signal or the difference between the propagation time reached through other paths. It can be said to be a step to increase the reliability of At this time, the preset fault location can be referred to as a randomly preset fault location.

On the other hand, the shortest path from an arbitrary preset fault location to the bus of the power system can be said to derive all the shortest paths for each bus and obtain all combinations of the shortest paths in the power system that can be calculated from the set fault location.

In this case, the shortest path derivation step (S230) may derive at least one or more shortest paths from the preset fault location to the bus of the power system using a Dijkstra algorithm. At this time, the Dijkstra algorithm can be said to be an appropriate algorithm to calculate the shortest path between each synchronization phase through the weight value and connection information when the shortest path is derived.

In the transmission line classification step, at least one transmission line existing on the shortest path derived from the shortest path derivation step (S230) in the transmission line classification unit 250 can be distinguished from each transmission line previously stored in the network connected to the power system. Yes (S250). The reason is that the weight of the time difference measured at both ends of the transmission line existing on the shortest path corresponds to the ratio of the time taken for the fault signal to propagate, but the time difference measured at both ends of the transmission line that does not exist on the shortest path This is because the weight of is not in accordance with the time difference of the corresponding transmission line due to the time difference of the radio signal arriving through another path.

In the initial failure propagation information definition step, the initial failure propagation information may be defined based on each initial weight value corresponding to at least one transmission line separated from the transmission line classification step (S250) in the initial failure propagation information definition unit 270. Yes (S270). In more detail, in the initial failure propagation information defining step (S270), after correcting each initial weight value corresponding to the at least one divided transmission line, the corrected weight value may be defined as the initial failure propagation information. This can be said to be a step to utilize past fault data information previously stored in the network connected to the power system.

At this time, each initial weight value correction may be corrected in consideration of the shortest path derived from the shortest path derivation step (S230). And correction can use a neural network learning algorithm. For an example of using the neural network learning algorithm, the description of Table 1 may be referred to.

The main fault location estimation step includes the reference fault propagation information measured from the reference fault propagation information measuring step (S100) in the main fault location estimating unit 300, and the initial fault propagation measured from the initial fault propagation information measuring step (S200). A fault location in a transmission line constituting the power system may be estimated in real time through a comparison of a correlation coefficient corresponding to the information (S300).

In more detail, the main failure location estimation step (S300) may be described with reference to FIG. 11.

11 is a flow chart showing a main fault location estimation step (S300) according to FIG.

As shown in FIG. 11, the main fault location estimation step (S300) may include a fault bus calculation step (S310) and a sub fault location estimation step (S330).

The faulty bus calculation step includes the reference fault propagation information measured from the reference fault propagation information measuring step (S100) in the faulty bus calculation unit 310, and the initial fault propagation information measured from the initial fault propagation information measuring step (S200). A faulty bus in which the corresponding correlation coefficient is maximum may be calculated (S310). This is a step to increase the reliability of fault location estimation by obtaining a pattern in which the weight values of each transmission line are combined, calculating the correlation coefficient between each pattern, determining the similarity, and obtaining the most suitable pattern location. have.

At this time, the fault bus calculation step (S310) includes the reference fault propagation information measured from the reference fault propagation information measuring step (S100) based on Equations 3 and 4 below, and the initial fault propagation information measuring step (S200). It is possible to calculate the fault bus with the maximum correlation coefficient corresponding to the initial fault propagation information measured from.

<Equation 3>

: 가중치벡터 평균값, mi: i번째 측정 기울기값,

: 측정벡터 평균값)(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)

<Equation 4>

,

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position)

In the sub fault location estimation step, the sub fault location estimation unit 330 performs a binary search on the transmission line connecting the faulty bus calculated from the faulty bus calculation step (S310) to find the fault location in the transmission line in real time. It can be estimated (S330). This can be said to be a step for implementing a step-by-step fault location estimation function using a binary search method optimized for fault location estimation in a transmission line.

In this case, in the sub-failure location estimation step (S330), a failure location in the transmission line may be estimated in real time based on Equation 5 below. This is the same as in FIG. 5.

<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches)

Although described and illustrated in connection with a preferred embodiment for illustrating the technical idea of the present invention above, the present invention is not limited to the configuration and operation as illustrated and described as described above, and deviates from the scope of the technical idea. It will be appreciated by those skilled in the art that many changes and modifications can be made to the present invention without. Accordingly, all such appropriate changes and modifications should be considered to be within the scope of the present invention.

100: reference fault radio wave information measuring unit
110: frequency signal measuring unit 130: accumulated signal calculating unit
150: slope value calculation unit 170: reference fault propagation information definition unit
200: initial failure radio wave information measuring unit
210: initial weight value definition unit 230: shortest path derivation unit
250: transmission line division unit 270: initial failure radio wave information definition unit
300: main fault location estimation unit
310: fault bus calculation unit 330: sub fault location estimation unit

Claims (20)

A reference fault propagation information measuring unit for measuring reference fault propagation information flowing from a Phasor measurement unit (PMU) of a plurality of electric buses constituting a power system to a transmission line connecting the buses;
Including; an initial failure propagation information measuring unit for measuring initial failure propagation information based on past failure data information previously stored in the network connected to the power system,
The initial failure propagation information measuring unit,
An initial weight value defining unit defining an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line; Wow
Includes; a shortest path derivation unit for deriving the shortest path to each bus of the power system from a preset fault location based on the defined initial weight value,
A transmission line dividing unit for dividing at least one transmission line existing on the derived shortest path from each of the previously stored transmission lines; Wow
An initial failure propagation information defining unit for correcting each initial weight value corresponding to the at least one divided transmission line based on a neural network learning algorithm taking into account the derived shortest route, and then defining the initial failure propagation information as initial failure propagation information; Includes,
Estimating a fault location in the transmission line in real time by comparing the reference fault propagation information measured from the reference fault propagation information measuring unit and a correlation coefficient corresponding to the initial fault propagation information measured by the initial fault propagation information measuring unit. A real-time power system fault location estimation system based on a fault signal propagation time comprising a main fault location estimation unit. The method of claim 1, wherein the reference failure propagation information measuring unit,
A frequency signal measuring unit for measuring a frequency signal from each of the synchronization phasers of a plurality of buses constituting a power system;
An accumulated signal calculator configured to generate a difference signal for each sampling corresponding to before and after a predetermined period of the measured frequency signal and calculate an accumulated signal for each synchronization phase based on the difference signal;
A slope value calculator configured to linearize the calculated accumulated signal to calculate a slope value for each synchronization phase; And
Real-time based fault signal propagation time including; a reference fault propagation information defining unit defining a difference value between the calculated slope values for each sync phase as a reference weight value corresponding to a difference between reference fault propagation times flowing through each transmission line Power system fault location estimation system. delete The method of claim 1, wherein the main failure location estimation unit,
A fault bus calculation unit for calculating a fault bus having a maximum correlation coefficient corresponding to the reference fault propagation information measured by the reference fault propagation information measuring unit and the initial fault propagation information measured by the initial fault propagation information measuring unit; And
A real-time power system fault location based on a fault signal propagation time including; a sub fault location estimating unit for estimating the fault location in the transmission line in real time by binary search of the transmission line connecting the calculated fault bus Estimation system. The method of claim 2, wherein the accumulated signal calculating unit,
Real-time power based on fault signal propagation time for calculating the accumulated signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the cumulative signal calculation equation represented by Equation 1 below. System fault location estimation system.
<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant) The method of claim 2, wherein the slope value calculation unit,
A real-time power system fault location estimation system based on a fault signal propagation time for calculating a slope value for each synchronization phase by linearizing the calculated accumulated signal according to the slope value calculation formula represented by Equation 2 below.
<Equation 2>

(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase) The method of claim 1, wherein the shortest path derivation unit,
A real-time power system fault location estimation system based on a fault signal propagation time for deriving at least one or more shortest paths from the preset fault location to the bus of the power system using a Dijkstra algorithm. The method of claim 2,
Real-time power system fault location estimation system based on a fault signal propagation time further comprising; an update unit for updating past fault data information by storing a reference weight value defined by the reference fault propagation information definition unit in a network connected to the power system . The method of claim 4, wherein the faulty bus calculation unit,
The correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit and the initial fault propagation information measured by the initial fault propagation information measuring unit based on Equations 3 and 4 below becomes maximum. A real-time power system fault location estimation system based on fault signal propagation time to calculate faulty buses.
<Equation 3>

(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)
<Equation 4>

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position) The method of claim 4, wherein the sub-failure location estimation unit,
A real-time power system fault location estimation system based on a fault signal propagation time for estimating a fault location in the transmission line in real time based on Equation 5 below.
<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches) A reference fault propagation information measuring step of measuring reference fault propagation information flowing from a Phasor measurement unit (PMU) of a plurality of electrical buses constituting a power system to a transmission line connecting the buses;
Including; initial failure propagation information measuring step of measuring initial failure propagation information based on past failure data information previously stored in the network connected to the power system,
The initial failure propagation information measuring step,
An initial weight value defining step of defining an initial weight value of each transmission line previously stored in a network connected to the power system as a physical length of each transmission line; Wow
Including; a shortest path derivation step of deriving the shortest path to each bus of the power system from a preset fault location based on the defined initial weight value,
A transmission line classifying step of dividing at least one transmission line existing on the derived shortest path from each of the previously stored transmission lines; Wow
An initial failure propagation information defining step of correcting each initial weight value corresponding to the at least one divided transmission line based on a neural network learning algorithm in consideration of the derived shortest route, and then defining the initial failure propagation information as initial failure propagation information; Includes,
Estimating a fault location in the transmission line in real time by comparing the reference fault propagation information measured from the reference fault propagation information measuring step and a correlation coefficient corresponding to the initial fault propagation information measured by the initial fault propagation information measuring unit. Main fault location estimation step; Real-time power system fault location estimation method based on a fault signal propagation time including. The method of claim 11, wherein the step of measuring the reference failure propagation information,
A frequency signal measuring step of measuring a frequency signal from each sync phase of a plurality of buses constituting a power system in a frequency signal measuring unit;
An accumulated signal calculating step of generating a difference signal for each sampling corresponding to before and after a predetermined period of the measured frequency signal by the accumulated signal calculating unit and calculating an accumulated signal for each synchronization phase based on the generated difference signal;
A slope value calculation step of calculating a slope value for each synchronization phase by linearizing the calculated accumulated signal in a slope value calculation unit; And
Including; a reference fault propagation information defining step of defining a difference value between the calculated slope values for each sync phase in the reference fault propagation information definition unit as a reference weight value corresponding to a difference between reference fault propagation times flowing through each transmission line; Real-time power system fault location estimation method based on fault signal propagation time. delete The method of claim 11, wherein the step of estimating the main fault location comprises:
A fault for calculating a fault bus in which a correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring step and the initial fault propagation information measured from the initial fault propagation information measuring step in the fault bus calculation unit is maximum Bus calculation step; And
In a fault signal propagation time including; a sub fault location estimation step of estimating a fault location in the transmission line in real time by binary search of the transmission line connecting the calculated fault bus by the sub fault location estimator. Real-time power system fault location estimation method based. The method of claim 12, wherein the calculating of the accumulated signal comprises:
Real-time power based on fault signal propagation time for calculating the accumulated signal for each synchronization phase based on the difference signal of each sampling corresponding to before and after a predetermined time of the measured frequency signal according to the cumulative signal calculation equation represented by Equation 1 below. System fault location estimation method.
<Equation 1>

(f(t): cumulative signal value, ROCOF (rate of change of frequency): differential signal value, t: time (seconds), n: number of signal samples, k: reference time constant) The method of claim 12, wherein the calculating of the slope value comprises:
A real-time power system fault location estimation method based on a fault signal propagation time for calculating a slope value for each synchronization phase by linearizing the calculated accumulated signal according to the slope value calculation formula represented by Equation 2 below.
<Equation 2>

(

: Slope value, t: time (seconds), Nw: number of samples in the time window, k: random variable, i: i-th sync phase) The method of claim 11, wherein the step of deriving the shortest path comprises:
A real-time power system fault location estimation method based on a fault signal propagation time for deriving at least one or more shortest paths from the preset fault location to a bus of the power system using a Dijkstra algorithm. The method of claim 12, wherein the network connected to the power system,
A real-time power system fault location estimation method based on a fault signal propagation time, which is a network in which past fault data information is updated by storing a reference weight value defined in the reference fault propagation information defining step by an update unit. The method of claim 14, wherein the step of calculating the faulty bus comprises:
The correlation coefficient corresponding to the reference fault propagation information measured from the reference fault propagation information measuring unit and the initial fault propagation information measured by the initial fault propagation information measuring unit based on Equations 3 and 4 below becomes maximum. Real-time power system fault location estimation method based on fault signal propagation time to calculate faulty bus.
<Equation 3>

(x, y|r: power system position variable, W(x,y,r): weight vector, M(x,y,r): measurement signal gradient difference vector, NL: number of vector samples, i: sigma variable, wi: the ith weight,

: Weight vector average value, mi: ith measurement slope value,

: Average value of measurement vector)
<Equation 4>

,

(x: bus number, W(x,x,0): weight vector calculated from bus x position, M(x,x,0): measurement gradient vector calculated from bus x position, y: bus number, W( y,y,0): weight vector calculated at bus y position, M(y,y,0): measurement gradient vector calculated at bus y position) The method of claim 14, wherein the step of estimating the sub-failure location comprises:
A real-time power system fault location estimation method based on a fault signal propagation time for estimating a fault location in the transmission line in real time based on Equation 5 below.
<Equation 5>

(r': unit distance from bus x, rx: unit distance from r'to the point close to bus x, ry: unit distance from r'to the point near bus y, W(x,y,r'): ( Weight vector calculated at x,y,r') position, M(x,y,r'): measurement gradient vector calculated at (x,y,r') position, D(n): binary search direction calculation function , n: sigma variable, Nb: number of binary searches)

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