CN117269666A

CN117269666A - Active power distribution network fault positioning method based on measurement data

Info

Publication number: CN117269666A
Application number: CN202311079520.1A
Authority: CN
Inventors: 蒋雯倩; 林秀清; 覃予鹏; 陈珏羽; 颜丹丹; 李金瑾; 唐志涛; 杨舟; 徐达; 包岱远; 程万旭; 张焜; 黄军力; 蔡翰举
Original assignee: Tianjin University; Guangxi Power Grid Co Ltd
Current assignee: Tianjin University; Guangxi Power Grid Co Ltd
Priority date: 2023-08-25
Filing date: 2023-08-25
Publication date: 2023-12-22

Abstract

The invention discloses a fault positioning method of an active power distribution network based on measurement data, which comprises the following steps: collecting state data of an operation load bus of a power distribution network; dividing the area of the power distribution network system; based on the regional division result, carrying out fault region identification; detecting a bus nearest to the fault in the fault region; and identifying a fault branch based on the bus closest to the fault, and completing fault positioning. The invention provides a method for dividing a power distribution network system into different areas by utilizing mu PMU line current measurement, which is designed aiming at unavoidable information of a smart electric meter and mu PMU in a future smart decision system. Meanwhile, a non-iterative forward and reverse scanning technology is adopted to estimate the line current and the bus voltage of a fault area. The invention defines the identification error index of the fault bus, the fault section and the fault distance. The invention does not need information of the type of the ground fault, and is suitable for balanced, unbalanced, grid-connected and island power distribution systems.

Description

Active power distribution network fault positioning method based on measurement data

Technical Field

The invention belongs to the technical field of power distribution network fault positioning, and particularly relates to an active power distribution network fault positioning method based on measurement data.

Background

Accurate and fast fault localization schemes facilitate faster fault clearance, reduced downtime, and faster system recovery. Thus, it helps to improve the power quality of the system and reduce fines imposed on the distribution company. In addition, faster fault localization and isolation helps to achieve the flexibility and self-healing capabilities that are being explored in the current intelligent power distribution system (Distribution System, DS) environment.

Fault location identification schemes have changed significantly over the past few years. This is mainly due to various problems and technical challenges brought about by the introduction of distributed generation (Distributed Generation, DG) and the enhancement of monitoring capabilities of the power distribution system. Firstly, after DG is accessed, the power distribution network is changed from an original passive network into a multi-terminal power supply network, the topology structure of the power distribution network becomes more and more complex, a large number of distributed power supply nodes are added to the original node number of the power distribution network, and the difficulty technology of circuit overload management and voltage adjustment is increased; secondly, after the DG is connected into the power distribution network, the running mode of the power distribution network is changed to change the trend direction of the system, and meanwhile, the size, the direction, the duration and the like of short-circuit current flowing through a feeder line are changed, so that the original protection device cannot meet the requirements; and the fault point still has short-circuit current to flow after the fault due to the DG, so that reclosing on the voltage-free side of the verification line cannot be overlapped, and a great challenge is brought to safe and stable operation of the power distribution network.

The above challenges include: the presence of multiple sources of fault current, variations in fault levels, bi-directional power flow, formation of high reliability DG subnetworks. For these reasons, relay protection has the potential to coordinate faults, which may lead to erroneous relay protection actions.

Therefore, the conventional impedance-based fault-finding scheme and the fault-finding scheme based on the monitoring of the operating state of the protection device are gradually eliminated. Furthermore, it is not possible to rely entirely on substation measurements in future DS, as it is emphasized that DS is operated as a set of smaller islands for technical and economic reasons. In this case, it is preferable to use data of monitoring devices (e.g., smart Meters (SM), intelligent electronic devices (Intelligent Electronic Device, IED) and phasor measurement units (Phasor Measurement Units, PMU)) distributed on the DS instead of data from a single location such as a substation.

At present, fault positioning methods of a power distribution network containing DG can be divided into two types, namely a ranging method, the method is used for rapidly measuring the distance between fault points according to different fault characteristics so as to determine the fault position, and the method is generally used for fault ranging of a high-voltage power transmission line and is represented by an impedance method, an S-wave injection method and a traveling wave method; the other type is a segment determining method, which is used for determining a fault area according to the characteristic that the fault overcurrent information detected by the intelligent electronic equipment before and after the fault is different, and is generally used for positioning the fault of the power distribution network.

Because of the monitoring devices at multiple sites in the DS, researchers are employing measurement matching schemes to identify fault locations. In these schemes, electrical parameters such as bus voltage and line current data obtained from the monitoring device are matched to voltages and line currents calculated using various techniques such as branch impedance (Z _bus ) A state estimate, and a trend assuming the location of the fault. The location of the smallest error between the measured and calculated parameters is considered the location of the possible failure.

Disclosure of Invention

The invention provides a fault positioning method of an active power distribution network based on measurement data, which aims to solve the problems existing in the prior art.

The technical scheme of the invention is as follows: a fault positioning method of an active power distribution network based on measurement data comprises the following steps:

A. collecting state data of an operation load bus of a power distribution network;

B. dividing the area of the power distribution network system;

C. based on the regional division result, carrying out fault region identification;

D. detecting a bus nearest to the fault in the fault region;

E. and identifying a fault branch based on the bus closest to the fault, and completing fault positioning.

Furthermore, the step A collects the state data of the operation load bus of the power distribution network, and the specific process is as follows:

firstly, measuring the root mean square value of voltage and power through a smart meter in a power distribution network;

the voltage and current in the form of phasors are then measured by a microphase measurement unit in the distribution network.

Furthermore, the step B performs area division on the power distribution network system, and the specific process is as follows:

firstly, acquiring a position of a micro-phasor measurement unit mu PMU configured in a power distribution network system;

then, based on the position of the micro-phasor measurement unit mu PMU, the power distribution network system is initially divided into areas.

Further, the step C performs fault region identification based on the region division result, and the specific process is as follows:

firstly, obtaining a region division result and a microphase measurement unit mu PMU in a region;

then, monitoring positive sequence line current in the region by a micro-phasor measurement unit mu PMU;

and finally, carrying out fault area identification and judging to obtain a fault area.

Further, the fault area identification specifically comprises the following steps:

firstly, utilizing a micro-phasor measurement unit mu PMU to monitor a region to obtain positive sequence line currents before and during a fault;

then, identifying whether the region fails by positive sequence line current;

then, when a fault occurs, the load current is far smaller than the fault current;

finally, if the positive sequence superposition current entering and leaving the fault area is far higher than that of the non-fault area, the fault area identified by the parameter is judged.

Further, step D detects the bus closest to the fault in the fault area, and the specific process is as follows:

and detecting and obtaining a bus closest to the fault in the fault area by adopting a non-iterative backward positive sweep algorithm.

Furthermore, step E identifies a faulty branch based on the bus closest to the fault, and completes the fault location, which specifically includes the following steps:

firstly, obtaining the actual effective value voltage measured by the intelligent ammeter;

then, obtaining the effective value voltages of all buses connected to the nearest fault bus;

then, calculating an error between the two effective value voltages;

finally, the branch connecting the bus and the bus closest to the fault is considered the faulty branch, which calculates and measures the voltage with the greatest error.

Further, step E identifies a faulty branch based on the bus closest to the fault, and completes fault location, including determining a fault distance, which specifically includes the following steps:

and (3) through iteration of the distance value, when the error function value takes the minimum value, the distance value is confirmed to be the real fault distance.

Further, step D requires verification of the load current during the fault during the bus detection closest to the fault in the fault area.

The beneficial effects of the invention are as follows:

the invention proposes to design for SM and mu PMU information that is unavoidable in future intelligent decision-making systems, mu PMU line current measurement being used to divide the distribution network system into different areas. Meanwhile, a fault area identification scheme capable of reducing the fault identification search space is provided. The line current and bus voltage of the fault area are estimated by adopting a non-iterative forward and reverse scanning technology. The invention defines the identification error index of the fault bus, the fault section and the fault distance.

The invention uses SM voltage measurements to calculate load current during a fault, helping to determine accurate fault current. The invention can detect faults under higher fault resistance, and can detect fault areas, buses and sections. The fault distance estimation is affected by the SM voltage measurement error and the system line parameter error, but both errors do not affect the identification of the fault section. The invention does not need information of the type of the ground fault, and is suitable for balanced, unbalanced, grid-connected and island power distribution systems.

Drawings

FIG. 1 is a schematic diagram of a frame of the present invention;

FIG. 2 is a schematic diagram of distribution network area division and fault area identification in the present invention;

FIG. 3 is a schematic diagram of fault branch identification in the present invention.

Detailed Description

The present invention will be described in detail below with reference to the drawings and examples:

as shown in fig. 1 to 3, an active power distribution network fault positioning method based on measurement data includes the following steps:

B. dividing the area of the power distribution network system;

D. detecting a bus nearest to the fault in the fault region;

Step A, collecting state data of an operation load bus of a power distribution network, wherein the specific process is as follows:

And B, carrying out regional division on the power distribution network system, wherein the specific process is as follows:

And C, based on the regional division result, carrying out fault region identification, wherein the specific process is as follows:

The fault area identification comprises the following specific processes:

then, identifying whether the region fails by positive sequence line current;

Step D, detecting the bus closest to the fault in the fault area, wherein the specific process is as follows:

a non-iterative backward positive sweep (non-iterative backward-forward sweepscheme, BFSS) algorithm is used to detect and derive the bus closest to the fault in the fault region.

And E, identifying a fault branch based on the bus closest to the fault to finish fault positioning, wherein the specific process is as follows:

then, calculating an error between the two effective value voltages;

And E, identifying a fault branch based on the bus closest to the fault to complete fault positioning, wherein the specific process comprises the following steps of:

Step D requires validation of load current during the fault during detection of the bus nearest the fault in the fault area.

Specifically, step D detects the bus closest to the fault in the fault area, and the specific process is as follows:

firstly, detecting a bus approaching a fault requires calculating fault current;

the fault period current measured by the microphase measurement unit mu PMU of the monitored area is then the sum of the fault period load current and the fault current.

Finally, when calculating the fault current, the load current during the fault needs to be known, and the load current is subtracted from the fault current measured by the micro-phasor measurement unit mu PMU, so as to obtain the fault current.

Example 1

A fault positioning method of an active power distribution network based on measurement data comprises the following steps:

A. the method comprises the following steps of collecting state data of an operation load bus of the power distribution network:

the more common measurement equipment in the distribution network comprises a Smart Meter (SM) and a micro-phasor measurement unit (microphasor measurement units, mu PMU), wherein the smart meter SM and the micro-phasor measurement unit mu PMU are installed on a load bus to realize the applications of voltage control, state estimation, power quality measurement, load prediction, demand side response, power outage management, load model prediction, island monitoring and control and the like.

The micro-phasor measurement unit mu PMU is relatively expensive to install, and is typically deployed only on the distributed energy (distributed energy resource, DER) bus and a few locations to facilitate region formation, while the smart meter SM is installed on the other load buses.

The microphase measurement unit mu PMU measures voltage and current in the form of phasors, and the smart meter SM measures the root mean square value of the voltage and power.

The invention utilizes the effective value voltage provided by the intelligent ammeter SM and the phasor voltage and current provided by the micro-phasor measurement unit mu PMU to perform fault location.

B. The power distribution network system is divided into areas, and the method specifically comprises the following steps:

in order to reduce the search space for the distribution network, the fault identification analysis is limited to fault (fault) areas, and the system is divided into different areas.

The formation of the region is based on the line current measurement of the micro-phasor measurement unit mu PMU, by which the region boundary, i.e. the bus on which the mu PMU is mounted, is determined by the position of the current transformer of the micro-phasor measurement unit mu PMU.

C. Based on the region division result, fault region identification is performed, specifically as follows:

the fault area, i.e. the fault area, is identified by monitoring the fault area by means of a microphase measurement unit mu PMU the obtained pre-fault and during-fault positive line currents.

In fig. 2, region a is monitored by microphase measurement units mu PMU on buses 1 and 4. Line current I ₀₁ And I ₃₄ Is the positive sequence line current flowing into region a, I _DER2 Is the distributed energy source positive sequence current flowing into region a.

Similarly, region b containing bus bars 4, 5 and 6 is monitored by micro-phasor measurement unit μpmu on bus bars 4 and 7. Line current-I ₃₄ And I ₇₆ Is a positive sequence line current, I _DER6 Is a distributed energy source positive sequence current flowing into the region b.

Assuming a fault between zone a bus bar 2 and bus bar 3, as shown in fig. 2, there is:

wherein the pre-fault currents entering the region a are respectivelyAnd-> And->Is given by the sum of the total prefault load current of the region +.>The sum of the currents in the fault state is expressed as:

wherein I is _FDER Is the sum of the DER contributions to the positive sequence fault current on the 6, 2 buses; i _F1 And I _F7 The fault current contribution values of the bus 1 and the bus 7 are respectively obtained by subtracting the formula (1) from the formula (2):

ΔI ₀₁ +ΔI ₃₄ +ΔI _DER2 ＝ΔI _LZa +I _F1 +I _F7 +I _FDER (3)

for adjacent non-faulty areas, the sum of the positive sequence superimposed currents entering the area b before the fault is:

-I ₃₄ ^pre +I ₇₆ ^pre +I _DER6 ^pre ＝I _LZb ^pre (4)

in fault conditions, the line current I is monitored on the bus 4 ₃₄ Micro-phasor measurement unit mu PMU measurement-I _F7 And the fault current contributed by DER 6.

Similarly, the positive sequence line current I measured by the micro-phasor measurement unit μPMU on bus 7 ₇₆ Including fault current I _F7 Now, the sum of the currents entering region b in the fault state can be written as:

subtracting equation (4) from equation (5) yields:

ΔI ₃₄ +ΔI ₇₆ +ΔI _DER6 ＝ΔI _LZb (6)

equation (3) and equation (6) are the sum of the positive sequence superimposed microphase measurement unit mu PMU line current and the DER injection current into the fault region and the non-fault region, respectively.

It can be observed from equation (3) that the sum of the mu PMU currents superimposed by the positive sequence of the fault region is equal to the sum of the positive sequence fault current of the fault region and the positive sequence load current variation of the fault region.

Similarly, the sum of the micro-phasor measurement unit μpmu currents of the positive sequence stack in the non-fault region is equal to the variation of the positive sequence load current in that region.

In the fault state, the load current is significantly less than the fault current. Thus, the area load current will vary much less than the fault current. The sum of the positive sequence line superimposed currents into or out of the fault region is significantly higher than in the non-fault region. In the proposed solution, the sum of the positive sequence line superimposed currents entering the region is therefore used as a parameter for fault region detection. The failure recognition parameter FZDP of the region i is expressed as:

where n is the number of mu PMUs, ΔI, of the monitored region _μpmu,ps Is the superimposed positive sequence current injection calculated by the measurement of the micro-phasor measurement unit mu PMU.

After detecting a fault, the FZDP values of all the areas are calculated, and the area with high FZDP value is regarded as a fault area. After the fault area is determined, further analysis is performed to determine the exact fault location.

More specifically, the analysis includes four parts, namely calculating fault current, determining the bus nearest to the fault by BNF, determining a fault section, and determining an accurate fault point on the fault section.

D. The bus closest to the fault is detected in the fault area as follows:

step d1, calculating fault current

In a fault state, the bus voltage of the power distribution network system can change greatly. This variation in voltage affects the current drawn by the load, depending on the type of load. The fault period current measured by the microphase measurement unit mu PMU of the monitored area is the sum of the fault period load current and the fault current.

Therefore, in calculating the fault current, it is necessary to know the load current during the fault. With smart meters, a load model on the feed line can be estimated. By knowing the pre-fault load current, load model, pre-fault voltage and during-fault voltage of the bus (only the static voltage dependent load is considered), the during-fault load current can be obtained. The load current before the fault can be obtained through state estimation, the load model is assumed to be known, and the bus voltage before the fault and during the fault can be obtained through the intelligent ammeter SM.

For a constant power load, consider the load current drawn at fault as:

wherein,and->Constant power load fault time and pre-fault current, +.>And->And the average bus voltage before and during the fault is obtained by the intelligent ammeter respectively.

For a constant impedance load, the load current generated at fault is expressed as:

in the method, in the process of the invention,and->The current before fault and the current at fault of the constant impedance load are respectively;

for constant current loading:

wherein,and->Is the current before and during the fault of the constant current load.

The area fault current calculation formula is:

wherein I is _fabc For fault current, l is the number of bus bars in the region,for the load current during bus failure obtained by formulas (8) - (10), I _Zin,abc The sum of the currents flowing into this region, measured for mu PMU, is expressed as:

step d2, detecting the bus closest to the fault

The invention adopts a non-iterative backward positive sweep frequency (non-iterative backward-forward sweepscheme, BFSS) algorithm, which consists of two parts of backward scanning to determine regional line current and forward scanning to determine regional bus voltage, and in order to obtain the regional line current by using a backward scanning program, a kirchhoff current law is applied to each bus from the last bus to the first bus.

For example, the line current (I _PQ,abc ) Is derived from the sum of all bus load currents connected outside of buses Q and Q, expressed as:

wherein I is _Li,abc Is the load current of the ith bus. After the line current is calculated, a forward scanning method is adopted to obtain the bus voltage.

In the invention, starting from the known mu PMU bus voltage, the remaining bus voltage of the breaking belt is calculated by using the series three-phase line impedance and the line current. The bus voltage of any Q connected to P can be expressed as:

V _Q,abc ＝V _P,abc -I _PQ,abc ×Z _PQ,abc (14)

wherein Z is _PQ,abc A three-phase impedance matrix for the lines connecting bus bars P and Q.

After the bus voltage of the area is calculated, the difference value between the effective value calculated by the forward scanning method and the bus effective value measured by the intelligent ammeter is considered, and an error index of the considered condition is formulated. For the case of a fault on the ith bus, the error index (e _BNF ) Expressed as:

wherein n is the number of regional buses, V _c,abc And V _m,abc To represent, calculate and measure the vector of the three-phase voltage of bus k, e _BNF The bus i with the smallest value is the bus with the fault.

E. Based on the bus closest to the fault, the fault branch is identified, and the fault positioning is completed, specifically as follows:

step e1, judging fault branches

Taking fig. 3 as an example, assume that the failure point is F in (a) ₁ The bus closest to the fault is bus3, and the bus voltage of No. 2 and No. 4 can be obtained in the step D assuming that the bus No. 3 has a fault in (b). In FIG. 3 (a), I ₂₃ Line current flowing from bus No. 2 to bus No. 3, I _3F For the current flowing to the fault point F1 of the No. 3 bus, I _4F Electric power flowing to F1 for bus No. 4And (3) flow. As can be seen from fig. 3 (a) and (b), the line current I at the bus3 fault and actual fault location F1 ₂₃ Is the same, and the line current is different for the considered case (bus fault No. 3) and the actual case (point F1 fault). It follows that there is an error in the voltage calculation of bus 4, while the calculated voltage of bus 2 is closer to the measured value. The voltage interpolation at this time is expressed as:

ΔV ₄ ＝I _3F ×Z _3F (16)

when the voltage of the bus 4 is calculated, the measured effective value of the smart meter SM is compared. In the formula (16), Z _3F Is the line impedance of bus3 to fault point F1.

Therefore, in order to identify the faulty branch, the error between the actual rms voltage measured by the smart meter SM and the calculated rms voltages of all the buses connected to the bus nearest to the fault is calculated. The branch connecting the bus and the bus closest to the fault, whose error in calculating and measuring the voltage is the largest, is considered the faulty branch.

Step e2, determining the fault distance

In order to determine the fault distance, the voltage of one of the fault branches (bus 3) and the corresponding line current (I) _23,abc ). The line current and the bus voltage can be obtained according to step e1 (assuming that bus3 fails, line current I23 and bus voltage V3 are obtained).

Meanwhile, the voltage of the bus on the other side of the fault branch, namely the bus 4, is calculated and compared with the SM measured value of the intelligent ammeter. As shown in fig. 3 (a), assuming that the fault is located at d from bus3, the root mean square voltage of the other end bus (bus 4) can be calculated as a function of the fault distance:

wherein I is _3F,abc The current flowing from the bus bar 3 to the fault point is expressed as:

I _3F,abc ＝I _23,abc -I _L3,abc (18)

I _F4 the current to bus 4 for the fault point is expressed as:

I _F4,abc ＝I _3F,abc -I _f,abc (19)

I _fabc obtained by (11). By iteratively changing the distance, the error between the measured voltage of the busbar 4 and the calculated voltage is calculated, resulting in an unknown distance d. For distance d _i The error is calculated as:

finally take e _d Distance d with minimum value _i Is the required fault distance.

The foregoing disclosure is merely illustrative of specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art will readily recognize that changes and modifications are possible within the scope of the present invention.

Claims

1. The utility model provides an active distribution network fault location method based on measurement data which is characterized in that: the method comprises the following steps:

B. dividing the area of the power distribution network system;

D. detecting a bus nearest to the fault in the fault region;

2. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: step A, collecting state data of an operation load bus of a power distribution network, wherein the specific process is as follows:

3. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: and B, carrying out regional division on the power distribution network system, wherein the specific process is as follows:

then, based on the position of the micro-phasor measurement unit [ mu ] PMU, the power distribution network system is initially subjected to regional division.

4. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: and C, based on the regional division result, carrying out fault region identification, wherein the specific process is as follows:

firstly, obtaining a region division result and a microphase measurement unit [ mu ] PMU in a region;

then, monitoring positive sequence line current in the region by a micro-phasor measurement unit [ mu ] PMU;

5. The method for locating faults in an active power distribution network based on measurement data of claim 4, wherein: the fault area identification comprises the following specific processes:

firstly, utilizing a micro-phasor measurement unit [ mu ] PMU monitoring area to obtain positive sequence line currents before and during a fault;

then, identifying whether the region fails by positive sequence line current;

6. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: step D, detecting the bus closest to the fault in the fault area, wherein the specific process is as follows:

7. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: and E, identifying a fault branch based on the bus closest to the fault to finish fault positioning, wherein the specific process is as follows:

then, calculating an error between the two effective value voltages;

8. The method for locating faults in an active power distribution network based on measurement data of claim 1, wherein the method comprises the steps of: and E, identifying a fault branch based on the bus closest to the fault to complete fault positioning, wherein the specific process comprises the following steps of:

9. The method for locating faults in an active power distribution network based on measurement data of claim 6, wherein: step D requires validation of load current during the fault during detection of the bus nearest the fault in the fault area.