US 2026/0169050 A1 · HIGH-SPEED LOCATION METHOD FOR HIGH IMPEDANCE FAULT IN DISTRIBUTION NETWORK

Abstract

The present application relates to the technical field of power system fault detection, discloses a high-speed location method for high impedance fault in distribution network based on directional frequency scanning. The high-speed location method includes, intercepting a zero-sequence current signal I0j collected by each of monitoring points of the distribution network and a bus zero-sequence voltage signal U0 of the distribution network, determining the fault occurrence time tf, extracting a first natural mode function to directly reconstruct a original fault signal, projecting a first natural mode function signal to the reference orthogonal vector group respectively, distinguishing the upstream and downstream of a fault point by a clustering algorithm. The method of constructing virtual reference direction by orthogonal vector group does not need to install voltage transformers at all measuring points, thus reducing hardware investment and maintenance costs, reducing dependence on physical hardware and greatly improving fault detection speed.

A high-speed location method for high impedance fault in a distribution network based on directional frequency scanning, comprising:

S1, collecting signal:
intercepting a zero-sequence current signal I0j collected by each of monitoring points of the distribution network and a bus zero-sequence voltage signal U0 of the distribution network, wherein j is a corresponding serial number of the monitoring points, [tf−T, tf+5T] is an interception time of the zero-sequence current signal, tf is a fault occurrence time, and T is a power frequency cycle of the power network;
S2, determining the fault occurrence time:
determining the fault occurrence time tr by analyzing the bus zero-sequence voltage signal U0;
S3, decomposing discrete Fourier and reconstructing a fault characteristic signal:
using the discrete Fourier decomposition to construct a directional frequency scanning strategy for the zero-sequence current signal I0j collected by the monitoring points, and extracting a first natural mode function to directly reconstruct a original fault signal;
S4, constructing and projecting a feature vector:
constructing a reference orthogonal vector group in a high-dimensional space, and projecting a first natural mode function signal to the reference orthogonal vector group respectively to generate a three-dimensional feature vector;
and
S5, fusing feature and clustering analysis:
distinguishing the upstream and downstream of a fault point by a clustering algorithm and locating a fault area by a clustering result based on the feature vector of a plurality of time scales;
wherein in the S4 step, the constructing the feature vector comprises:
S401, designing a set of mutually orthogonal vector groups {right arrow over (a)} and {right arrow over (b)} for signal projection, and the expression is:
{
a
⇀
=
{
A
1
⁢
cos
⁡
(
ω
0
⁢
t
k
+
φ
)
}
b
⇀
=
{
A
2
⁢
cos
⁡
(
ω
0
⁢
t
k
+
φ
-
π
2
)
}
A
1
·
A
2
>
0
;
wherein w0 is an angular frequency of a power grid, A1, A2, φ└R, tk∈[tf, tf+0.5T·P], P and k are positive integers, tk+1−tk=1/fc, and fc is an actual sampling frequency of a current sensor;
a typical values are:
A1=A2=1, j=0, fc=10 kHz, tk+1−tk=10−4;
and
S402, projecting the first natural mode function signal to the vector group, taking P=1 and fc to the actual sampling frequency of the current sensor, intercepting the first natural mode function calculated at all of the monitoring points corresponding to [tf, tf+0.5T] time period, recording the first natural mode function obtained at a j-th monitoring point as
I
0
⁢
j
Re
,
0.5
T
,
and projecting
I
0
⁢
j
Re
,
0.5
T
to the orthogonal vector group proposed in step S401 to obtain the projection result:
{
I
0
⁢
j
Re
,
0.5
T
,
a
⇀
=
arccos
⁢
I
0
⁢
j
Re
,
0.5
T
·
a
⇀

I
0
⁢
j
Re
,
0.5
T

×

a
⇀

I
0
⁢
j
Re
,
0.5
T
,
b
⇀
=
arccos
⁢
I
0
⁢
j
Re
,
0.5
T
·
b
⇀

I
0
⁢
j
Re
,
0.5
T

×

b
⇀

;
wherein in the S4 step, a result of a feature vector generation is expressed in polar coordinates:
S403, obtaining a set of three-dimensional vectors as follows:
M
j
=
(
I
0
⁢
j
Re
,
0.5
T
,
〈
I
0
⁢
j
Re
,
0.5
T
,
a
→
〉
,
〈
I
0
⁢
j
Re
,
0.5
T
,
b
→
〉
+
π
)
;
and the set of three-dimensional vectors can be correspondingly expressed as J pairs of vector groups in polar coordinates:
{
P
⇀
j
,
a
⇀
=
(
❘
"\[LeftBracketingBar]"
I
0
⁢
j
Re
,
0.5
T
❘
"\[RightBracketingBar]"
,
I
0
⁢
j
Re
,
0.5
T
,
a
⇀
)
P
⇀
j
,
b
⇀
=
(
❘
"\[LeftBracketingBar]"
I
0
⁢
j
Re
,
0.5
T
❘
"\[RightBracketingBar]"
,
I
0
⁢
j
Re
,
0.5
T
,
b
⇀
+
π
)
;
S404, taking all j=1, 2, 3, . . . , J, if the following inequality can be established:
max
⁢
{
?
,
?
}
-
min
⁢
{
?
,
?
}
>
max
⁢
{
?
,
?
}
-
min
⁢
{
?
,
?
}
;
?
indicates text missing or illegible when filed
wherein the orientation quantity group
{
P
V
j
,
a
V
}
is used as the characteristic vector group for judging the high impedance fault, otherwise, the orientation quantity group
{
P
V
j
,
b
V
}
is used as the feature vector group for judging the high impedance fault;
S405, recording the feature vector group obtained in the S404 step to judge the high impedance fault as
{
P
V
j
0.5
T
}
;
and
S406, repeating the steps S402-S405 with P=2 and P=4, respectively, and obtaining two other groups of the feature vector groups
{
P
V
j
T
}
⁢
and
⁢
{
P
V
j
2
⁢
T
}
for judging the high impedance fault.

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High-speed location method for high impedance fault in distribution network

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High-speed location method for high impedance fault in distribution network

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Abstract

Claims9