CN112467724A - Low-voltage distribution network fault studying and judging method - Google Patents
Low-voltage distribution network fault studying and judging method Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
- H02J3/00125—Transmission line or load transient problems, e.g. overvoltage, resonance or self-excitation of inductive loads
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
- H02J3/0012—Contingency detection
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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Abstract
The invention discloses a low-voltage distribution network fault studying and judging method which is based on power failure information of a low-voltage electric meter, combines a medium-low voltage electric topological relation, fuses fault information of a medium-low voltage stop battery, establishes a fault diagnosis and analysis model of a medium-low voltage electric network and realizes an electric network low-voltage fault analysis and positioning function. The method comprises the steps of firstly obtaining an external alarm signal, screening and filtering out an interference signal, then developing low-voltage fault study and judgment, accurately positioning a fault source at a single-family fault, a low-voltage branch line fault, a distribution transformer area fault and a medium-voltage feeder line fault, matching with a power failure event in a power failure information pool, automatically generating a first-aid repair work order, and distributing the first-aid repair work order to first-aid repair personnel to realize rapid and active first-aid repair.
Description
Technical Field
The invention relates to the field of power grid production and operation, in particular to a low-voltage power distribution network fault studying and judging method.
Background
With social development, the living standard is continuously improved, people also put forward higher requirements on power supply reliability and power supply service level, and the initiative degree of a power distribution network needs to be further improved. The distribution system is used as an important link of electric energy production, transmission and use, has the obvious characteristics of wide distribution and more equipment, influences normal power supply work when faults occur, even leads to the breakdown of the electric power system, particularly in the aspect of low-voltage distribution networks, the faults occur frequently, the content of research and judgment on the faults of the low-voltage distribution networks at home and abroad at present is less, the research on the key characteristic quantity of low-voltage fault information in service systems such as a metering automation system, a distribution automation system, a 95598 fault reporting system and the like is lacked, and a large amount of effective information is wasted.
In the current low-voltage emergency repair mode, after a fault occurs, an emergency repair point passively informs a site to confirm the condition, and emergency repair resources are allocated according to the size of the fault to implement emergency repair work. Failure study and judgment in the emergency repair work is inaccurate, the problems of phase loss, grounding and the like of a low-voltage line cannot be effectively studied and judged, and certain influence is caused on the development of the modular emergency repair work. Each power supply bureau in Guangdong reports about tens of thousands of fault work orders every year, the fault types are mainly low-voltage, the fault reason analysis mainly depends on experience and on-site inspection processing, an automatic and informatization supporting means is lacked, low-voltage GIS and metering automatic meter reading information cannot be utilized, and the processing workload is large. Therefore, the research on the active low-voltage fault detection and research and judgment method is of great significance for improving the low-voltage fault diagnosis and treatment efficiency of the power supply bureau.
Disclosure of Invention
The invention provides a low-voltage distribution network fault studying and judging method which is based on power failure information of a low-voltage electric meter, combines medium and low voltage electric topological relation, fuses fault information of a medium-voltage stop battery, establishes a fault diagnosis and analysis model of a medium and low voltage electric network and realizes the function of analyzing and positioning low-voltage faults of the electric network.
The final studying and judging results of the low-voltage fault studying and judging analysis can be divided into single-family faults, low-voltage branch line faults, distribution transformer area faults and medium-voltage feeder line faults according to the difference of finally positioned fault equipment. The specific process is as follows:
(1) inquiring low-voltage user alarm data in a polling mode;
(2) grouping low-voltage outgoing lines through low-voltage alarm measuring point identifiers, and identifying which group of low-voltage outgoing lines the alarm signals belong to;
(3) calculating the percentage of the alarm users in the total number of users under the low-voltage outgoing line, and if the percentage is lower than P1(P1 can be configured according to the actual situation), indicating that the alarm signal is caused by single-user fault;
(4) when the percentage of the alarm users in the total number of users under the low-voltage outgoing lines exceeds P1, grouping the power-off low-voltage outgoing lines according to the distribution transformer, and identifying which group of distribution transformer the power-off low-voltage outgoing lines belong to;
(5) calculating the percentage of the low-voltage outgoing lines in power failure under the distribution transformer to the total number of the low-voltage outgoing lines, and if the percentage is lower than P2(P2 can be configured according to the actual situation), indicating that the alarm signal is caused by the fault of the low-voltage branch line;
(6) when the percentage of the low-voltage outgoing lines in the power failure under the distribution transformer to the total number of the low-voltage outgoing lines exceeds P2, grouping the power failure distribution transformer according to the dynamic power supply feeder, and identifying which medium-voltage feeder the power failure distribution transformer belongs to;
(7) each group of distribution transformers respectively analyzes the nearest common upstream switch;
(8) analyzing the power supply range of the switch, and extracting the total number of distribution transformers in the switch;
(9) and calculating the percentage of the power failure distribution transformer to the total number of the distribution transformers, and if the percentage is lower than P3(P3 can be configured according to actual conditions), indicating that the alarm signal is caused by the fault of the distribution transformer area. If the percentage of the power failure distribution transformer to the total number of the distribution transformers exceeds P3, the alarm signal is caused by the medium-voltage feeder line fault;
(10) matching a distribution transformer fault or a medium-voltage feeder fault which occurs during fault study and judgment with a power failure pool, and inquiring whether a fault power failure event exists in a power failure pool or not;
(11) if the stopped battery does contain the fault power failure event, the stopped battery can inquire the detailed event information according to the ID of the corresponding power failure event;
(12) if the power failure event is not contained in the stopped battery, the power failure event needs to be newly added in the power failure information pool, and meanwhile, the distribution transformer or the medium-voltage feeder power failure influence range is analyzed, and the power failure influence equipment is recorded in a power failure equipment table of the power failure information pool.
Furthermore, the power failure event information obtained by low-voltage fault study and judgment can automatically generate an emergency repair work order, and the emergency repair work order is distributed to emergency repair personnel to carry out emergency repair work in an automatic mode.
Further, false alarm signals may exist in the fault alarm signals, some alarm signals can be recovered by themselves, some alarm signals are caused by interference, the signals need to be filtered, and a deep learning method is adopted during filtering, so that real fault alarm signals are obtained through model construction, training and testing.
By the method provided by the invention, the diagnosis and study of the faults of the low-voltage distribution network can be quickly realized, the faults can be actively sensed and positioned as far as possible before the users report the faults, the rush-repair work can be timely carried out, the satisfaction degree of the users is improved, the scientificity and the accuracy of the fault study and study are improved, the defect of manual field study and study in the past is avoided, and the work burden of distribution network production operators is reduced.
Drawings
FIG. 1 is a schematic diagram of a low-voltage distribution network topology according to an embodiment of the present invention;
FIG. 2 is a flow chart of low-voltage fault diagnosis according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating alarm processing according to an embodiment of the present invention;
FIG. 4 is a flow chart of a root cause trip switch analysis according to an embodiment of the present invention;
Detailed Description
In order to make the technical contents of the present invention clearer, the following describes the embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of a typical medium-and-low-voltage distribution network topology structure under one feeder line, wherein a plurality of distribution transformers are connected to one medium-voltage feeder line led out from a transformer substation, a plurality of low-voltage outgoing lines are arranged under each distribution transformer, each low-voltage outgoing line comprises a low-voltage branch switch and a large number of low-voltage users, and each low-voltage user has a measurement point.
As shown in fig. 2, the final studying and judging result of the low-voltage fault studying and judging analysis can be divided into a single-family fault, a low-voltage branch line fault, a distribution transformer area fault and a medium-voltage feeder line fault according to the difference of the finally positioned fault devices. The specific analysis flow is as follows:
(1) inquiring low-voltage user alarm data in a polling mode;
the low-voltage user alarm data can be inquired in two modes, and the time point and the time period can be selected for inquiry.
And when the time point T is selected, acquiring the low-voltage user alarm data which is still in a power-off state at the current time point T.
And when the time period T is selected, acquiring low-voltage user alarm data of the power failure alarm occurring in the time period T.
(2) Grouping low-voltage outgoing lines through low-voltage alarm measuring point identifiers, and identifying which group of low-voltage outgoing lines the alarm signals belong to;
(3) calculating the percentage of the alarm users in the total number of users under the low-voltage outgoing line, and if the percentage is lower than P1(P1 can be configured according to the actual situation), indicating that the alarm signal is caused by single-user fault;
(4) when the percentage of the alarm users in the total number of users under the low-voltage outgoing lines exceeds P1, grouping the power-off low-voltage outgoing lines according to the distribution transformer, and identifying which group of distribution transformer the power-off low-voltage outgoing lines belong to;
(5) calculating the percentage of the low-voltage outgoing lines in power failure under the distribution transformer to the total number of the low-voltage outgoing lines, and if the percentage is lower than P2(P2 can be configured according to the actual situation), indicating that the alarm signal is caused by the fault of the low-voltage branch line;
(6) when the percentage of the low-voltage outgoing lines in the power failure under the distribution transformer to the total number of the low-voltage outgoing lines exceeds P2, grouping the power failure distribution transformer according to the dynamic power supply feeder, and identifying which medium-voltage feeder the power failure distribution transformer belongs to;
(7) each group of distribution transformers respectively analyzes the nearest common upstream switch;
(8) analyzing the power supply range of the switch, and extracting the total number of distribution transformers in the switch;
(9) and calculating the percentage of the power failure distribution transformer to the total number of the distribution transformers, and if the percentage is lower than P3(P3 can be configured according to actual conditions), indicating that the alarm signal is caused by the fault of the distribution transformer area. If the percentage of the power failure distribution transformer to the total number of the distribution transformers exceeds P3, the alarm signal is caused by the medium-voltage feeder line fault;
(10) matching a distribution transformer fault or a medium-voltage feeder fault which occurs during fault study and judgment with a power failure pool, and inquiring whether a fault power failure event exists in a power failure pool or not;
(11) if the stopped battery does contain the fault power failure event, the stopped battery can inquire the detailed event information according to the ID of the corresponding power failure event;
(12) if the power failure event is not contained in the stopped battery, the power failure event needs to be newly added in the power failure information pool, and meanwhile, the power failure influence range of the distribution transformer or the medium-voltage feeder is analyzed, and the power failure influence equipment is recorded into the power failure equipment in the power failure information pool.
As shown in fig. 3, the power failure event information obtained by the low-voltage fault study and judgment can automatically generate an emergency repair work order, and the emergency repair work order is distributed to emergency repair personnel to carry out emergency repair work in an automatic mode.
False alarm signals may exist in the fault alarm signals, some alarm signals can be recovered automatically, some alarm signals are caused by interference, the signals need to be filtered, and a deep learning method is adopted during filtering, so that real fault alarm signals are obtained through model construction, training and testing.
Specifically, the deep learning adopts a long-time memory model (LSTM) to screen the alarm signals. The LSTM model comprises an input layer, a hidden layer and an output layer, wherein the input layer processes one alarm signal each time, splits an alarm signal sentence into words, and converts each word into a multidimensional digital vector; the hidden layer automatically extracts data features; and the output layer calculates the probability of belonging to each category according to the data characteristics, outputs the classification result, and marks a real alarm signal result label and an alarm signal result label caused by interference.
The power failure information pool mainly collects power failure information in each service system, the power failure information is a place for managing shared power failure events, and if the obtained fault signals are distribution transformation or switch alarm information, the fault information is directly written into a battery.
Specifically, taking a switch trip alarm as an example, the switch trip alarm may have associated trip, a root cause trip switch is searched first, then power supply range analysis is performed on the root cause trip switch, equipment information such as influencing distribution transformation and switching is stored, and a power failure event is generated and stored in a power failure information pool table.
Specifically, the process of finding the root-cause trip switch is shown in fig. 4, and the received switch alarm signals of the current batch are firstly analyzed for the power supply path, and the switch alarm signals received in the previous batch are combined, because the arrival sequence of the alarm information related to trip is possibly inconsistent, but the time difference is not too long, and the alarm information is mostly distributed in two adjacent polling period queries, and the polling is performed once in the shortest 5 seconds. According to the power supply path of the switch, the upstream and downstream relation between the switches is found, the switches with the power supply relation are divided into a group, the most upstream power supply switch of each group is found, the most upstream power supply switch is identified as the root power failure switch of each group, the root power switch which is divided into a group of switches with the batch of switches is updated, and the root power switch of the batch of switches is set.
Claims (5)
1. A low-voltage distribution network fault studying and judging method is characterized in that a fault diagnosis and analysis model of a medium-low voltage power grid is established by combining medium-low voltage electric topological relation and fusing fault information of medium-low voltage stop batteries based on power failure information of a low-voltage electric meter, so that a low-voltage fault analysis and positioning function of the power grid is realized.
2. The method according to claim 1, wherein the final study and judgment results of the low-voltage fault study and judgment analysis can be classified into single-family faults, low-voltage branch line faults, distribution transformer area faults and medium-voltage feeder line faults according to different finally positioned fault devices. The specific criteria are as follows:
when the percentage of the alarm users in the total number of the users under the low-voltage outgoing line is lower than a certain value, the alarm signal is caused by single-user fault;
when the percentage of the low-voltage outgoing lines with power failure in the distribution transformer to the total number of the low-voltage outgoing lines is lower than a certain value, indicating that the alarm signal is caused by the fault of the low-voltage branch line;
when the percentage of the power failure distribution transformer to the total number of the distribution transformers is lower than a certain value, the alarm signal is caused by the fault of the distribution transformer area;
when the percentage of the power failure distribution transformer to the total number of the distribution transformers is higher than a certain value, the alarm signal is caused by the medium-voltage feeder line fault.
3. The method according to claim 1, wherein the distribution transformer fault or the medium voltage feeder fault occurring during the fault study and judgment is matched with the outage pool to inquire whether the outage event exists in the outage pool, and if the outage event does not exist in the outage pool, the outage event needs to be newly added to the outage information pool.
4. The method of claim 1, wherein the power failure event information obtained from the low voltage fault study and judgment automatically generates a repair order, and the repair order is distributed to repair personnel for repair work.
5. The method of claim 1, wherein the fault warning signal is filtered by deep learning to remove interference signals and obtain a true fault warning signal.
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Cited By (6)
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| CN113591319A (en) * | 2021-08-06 | 2021-11-02 | 广东电网有限责任公司广州供电局 | Method and device for studying and judging metering shunt alarm fault in power grid |
| CN113759165A (en) * | 2021-08-13 | 2021-12-07 | 贵州电网有限责任公司遵义供电局 | Power distribution network fault power failure perception analysis method and equipment |
| CN114156865A (en) * | 2021-11-01 | 2022-03-08 | 国网天津市电力公司电力科学研究院 | Low-voltage distribution network topology generation and fault prediction method considering state perception |
| CN115983519A (en) * | 2023-03-20 | 2023-04-18 | 国网江西省电力有限公司电力科学研究院 | Digital operation and maintenance method and system for power distribution network and readable storage medium |
| CN116093937A (en) * | 2023-03-22 | 2023-05-09 | 国网江西省电力有限公司电力科学研究院 | Layered research and judgment method and system for power failure faults of 10kV line and below |
| CN117310333A (en) * | 2023-10-10 | 2023-12-29 | 国网江苏省电力有限公司扬州供电分公司 | High-low voltage overall process fault studying and judging method based on key factor filtering method |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113591319A (en) * | 2021-08-06 | 2021-11-02 | 广东电网有限责任公司广州供电局 | Method and device for studying and judging metering shunt alarm fault in power grid |
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| CN114156865A (en) * | 2021-11-01 | 2022-03-08 | 国网天津市电力公司电力科学研究院 | Low-voltage distribution network topology generation and fault prediction method considering state perception |
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| CN115983519A (en) * | 2023-03-20 | 2023-04-18 | 国网江西省电力有限公司电力科学研究院 | Digital operation and maintenance method and system for power distribution network and readable storage medium |
| CN115983519B (en) * | 2023-03-20 | 2023-08-15 | 国网江西省电力有限公司电力科学研究院 | Digital operation and maintenance method and system for power distribution network and readable storage medium |
| CN116093937A (en) * | 2023-03-22 | 2023-05-09 | 国网江西省电力有限公司电力科学研究院 | Layered research and judgment method and system for power failure faults of 10kV line and below |
| CN117310333A (en) * | 2023-10-10 | 2023-12-29 | 国网江苏省电力有限公司扬州供电分公司 | High-low voltage overall process fault studying and judging method based on key factor filtering method |
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Application publication date: 20210309 |