JPH03251022A - Device for monitoring abnormal state of distribution line - Google Patents

Abstract

PURPOSE:To enable failure in a distribution line to be detected at a failure prediction stage by providing a waveform classification means at each sub station and by analyzing and classifying an abnormal waveform of zero-phase voltage/current of the distribution line automatically. CONSTITUTION:A waveform classification means is provided at each sub station 11-n and an abnormal waveform of zero-phase voltage and zero-phase current is automatically collected for each waveform classification. Also, a failure prediction means 27 of a master station 40 detects a failure section from output details of an abnormal cause data which is determined and extracted by an abnormal cause determination means 26 to enable a failure in the distribution line to be detected readily at a failure prediction stage, thus preventing the failure from occurring and enabling the failed part to be removed and recovered readily. Also, data accumulation for analyzing an abnormal waveform of zero-phase voltage and zero-phase current which occur in the distribution line can be automatically performed at a level of each sub station 11-n. Further, it is possible to enable accuracy for determining correlation between an abnormal waveform and a failure in the distribution line to be less subject to influence of system coefficients of the distribution system.

Description

[Detailed description of the invention] [Industrial application field]

This invention classifies abnormal waveforms of zero-sequence voltages and zero-sequence currents that occur in distribution lines, automatically collects abnormal waveforms, and detects abnormal states of distribution lines by predicting failures of distribution lines from these abnormal waveforms. This relates to a monitoring device.

[Conventional technology]

FIG. 4 is a block configuration diagram showing a system for collecting abnormal waveforms of zero-sequence voltage Vo and zero-sequence current 1o at the time of a distribution line failure and detecting distribution line failure prediction, which is a conventional device of this type. In the figure, 1 is the distribution transformer, 2 is the busbar of the distribution substation connected to this distribution transformer 1, L is the distribution line connected to the bus 2 of the distribution substation, and CB is the distribution line. A circuit breaker connected between the busbar 2 and the distribution substation
CT is a zero-sequence current detector (hereinafter referred to as a zero-sequence current transformer), which detects the zero-sequence current of each distribution line and uses its output to detect the ground fault direction of each distribution line connected to the secondary side. It is designed to be input to relay 67G. In addition, ZCT2 is another zero-phase current transformer, CT is a current transformer, 51S is an overcurrent relay for short circuit, and GPT is a grounding transformer connected to bus 2 of the distribution substation. The ground fault overvoltage relay OVG operates by detecting the zero-sequence voltage that occurs in the event of a ground fault, and the ground fault overvoltage relay OVG operates by detecting the direction of the ground fault from the phase relationship between this zero-sequence voltage and the zero-sequence current of each distribution line. A winding direction relay 67G is connected. Furthermore, 10 is an abnormal waveform analysis section. In addition,
The above-mentioned distribution line is connected to the bus 2 of the distribution substation in multiple systems, and the above-mentioned zero-phase current transformer Z C is connected to the distribution line of each system.
TC,z CT2. A current transformer CT and a circuit breaker CB are respectively connected. SHl is the zero-phase current transformer ZC of each distribution line.
T, is a sample hold circuit that samples and holds each zero-phase current transformer 101 to IOr+ detected, and SH, is a zero-phase voltage (2) detected by the tertiary winding of the grounding transformer GPT. Sample and hold circuit, SH3, samples and holds
is a sample hold circuit that samples and holds the phase reference line voltage Vs detected by the secondary winding of the grounding transformer GPT, MPX is a sample hold circuit S H+,
A multiplexer that selects and inputs each output of S Ht and S Hs one by one; A/D is an analog/digital converter that digitally converts the output of the multiplexer MPX; 3
monitors the output of the analog/digital converter A/D,
A startup detector that activates the microprocessor CPU to start calculations when an input exceeding a preset value is detected, ROM is a program memory that stores programs for executing various calculation processes, and RAM is a variety of RAM, a temporary storage memory that temporarily stores data, is an abnormal waveform data memory, RAM, that stores zero-sequence voltage (hereinafter referred to as ■) and zero-sequence current (hereinafter referred to as i) generated on the distribution line. ■ is stored in the abnormal waveform data memory RAM. ,I. Abnormal waveform analysis data memory (ROM) that stores data obtained by analyzing abnormal waveforms of data is waveform classification data that stores field data obtained from the actual power distribution system or multiple reference data obtained experimentally in advance. Memory, ROM
z is the waveform classification data memory ROM, a cause-specific data memory that specifically stores cause data corresponding to the standard data, and the CPU is each of the above memories RAM+, RA Mt.
, ROM+, and R0M2 utilize the data stored in the microprocessor to execute the desired arithmetic processing according to the program in the program memory ROM. 4 is a controller for controlling the display of the display CRT, and PI3 is a process input/output device for outputting an alarm. Further, in FIG. 5, 20 is a detection means for detecting the zero-sequence voltage and zero-sequence current of the distribution line, and 21 is a signal conversion means for sampling the zero-sequence voltage and zero-sequence current from the detection means 20 and converting them into digital data. , 22 is an abnormal waveform detection means for detecting abnormal waveforms of zero-sequence voltage and zero-sequence current using data from the signal conversion means 21; 23 is a waveform analysis means for analyzing the abnormal waveform; and 24 is a signal obtained from the waveform analysis means 23. 25 is a waveform classification memory that stores abnormal waveform data groups for each waveform classification; 26 is the nine analysis classifications according to the waveform classification results; An abnormality cause determining means 27 determines the cause of an abnormality corresponding to the waveform data, and a failure prediction means 27 predicts a failure of the distribution line based on the cause of the abnormality. Next, the operation shown in FIG. 4 will be explained below with reference to the flowcharts shown in FIGS. 5 and 6. First, if there is no abnormality in any of the distribution lines, power is normally supplied to the loads connected to each section. On the other hand, if a ground fault occurs in any of the above distribution lines, the failure point, ground and zero-phase current transformer ZCT,
A zero-sequence current flows through. Therefore, a zero-phase secondary current flows through the ground fault direction relay 67G connected to the secondary side of the zero-phase current transformer ZCT, and a zero-phase voltage is input via the grounding transformer GPT. This works. On the other hand, at this time, the ground fault overvoltage relay OVC detects the zero-sequence voltage that occurs at the time of the accident and operates. Operating output of this ground fault overvoltage relay OVG and ground fault direction relay 67G
When the logical product of the operation outputs is established, the circuit breaker CB is opened after a predetermined time. Note that protection operations for ground faults occurring in other power distribution vALs are performed in the same manner as described above. On the other hand, if a failure such as a ground fault occurs in any of the above-mentioned distribution lines, the zero-phase current transformer ZCT2 and the grounding Zero-sequence voltage V0. The zero-phase voltages I0 are each detected (step 5T1), and these, together with the phase reference line voltage V3, are transmitted to the sample and hold circuits S H+ to SH3 that constitute the signal conversion means 21, for example, 3
The data is sampled at intervals of 0.06 (step 5T2). Next, the sampled data is temporarily held and then taken in one after another by the multiplexer MPX. This is how ■ was captured. , I0 data is sent to the analog/digital converter A/ which constitutes the signal converting means 21.
The data is converted into digital data by the microprocessor CPU and stored in the temporary memory RAM. On the other hand, the activation detector 3 adds the sampled data for one cycle to obtain an average value, and calculates the average value. , Io is calculated every cycle for each input (step 5T3),
It is determined whether the average value exceeds a specified value (step 5T4). Here, if it is determined that the value exceeds the specified value, the digital data is stored in the temporary storage memory RA.
M (step 5T5), and output after a certain period of time after exceeding the specified value and falling below the specified value. Vo, I0 abnormal waveform data memory RA
Store it in M (step 5T7). Then, the processing from steps ST3 to ST7 is executed in the abnormal waveform detection means 22. Next, the above abnormal waveform data is subjected to waveform analysis (hereinafter referred to as FFT analysis) by fast Fourier transform for each occurrence number by the waveform analysis means 23 (
Step 5T8). This waveform analysis means 23 sets one cycle of the phase reference line voltage ■ as an analysis cycle, and then performs FFT analysis using the sampling data during the analysis cycle to detect direct current, fundamental wave, and high frequency components. effective value, peak value +V
The OIo phase angle is calculated (step 5T8). Here, each zero-sequence current 1 (II to Ion
uses the line with the largest peak value, and Vo. If both Io and Io have abnormal waveforms, ■. . ■. It is confirmed that +IO occurs within a certain period of time, that is, that Vo and Io occur due to the same failure cause. Then, the analysis data of such an abnormal waveform is stored in the analysis data memory RAM (step 5T9).
). Next, the stored analysis data is stored in the waveform classification data memory ROM, and is compared with reference waveform data (step 5T10), and it is determined whether or not these items of comparison match (step STI 1), they match. If so, a waveform classification number is assigned (step 5T12). In addition, the cause corresponding to such a waveform classification number is extracted from the cause-specific data stored in the cause-specific data memory ROM2 (step 5T13), and the cause is displayed on the display CRT or an alarm is issued as an alarm output. output to the device (
Step ST14). In addition, if the verification targets do not match in step 5TII, extract all the waveform classification data in step STI 5), and when the extraction is finished, assign a unique waveform number as new abnormal data in step 5T16). Execute 5T13 and below. Through such processing, the display CRT displays the following information:
■. ,■. The waveform, distribution line number, abnormality occurrence time, waveform classification 2 occurrence cause, etc. are displayed, and failures can be concretely predicted. 7(a) is stored in the waveform classification data memory ROM. The waveform classification data of FIG. 7(b) is the same <1. shows the waveform classification data of , and exhibits a waveform pattern corresponding to a failure accident in the distribution line L. Also, ■ like this. ,
The cause of the abnormality corresponding to the waveform classification data of Io is obtained from a failure example in an actual power distribution system or experimentally, and is shown in FIG. As you can see in this table,■. The waveforms from AC wave Va to irregular distorted wave Vi are in the failure (including cases where the cause is unknown) region. Therefore, as you can see from this table, ■. If is an AC wave Va and Io is a rectangular wave, the cause of the failure in the distribution line can be determined to be, for example, a different-phase ground fault, and by confirming this as failure prediction information for the distribution line, it can be determined that deterioration is progressing. Natural phenomena such as abnormalities in power distribution equipment, contact with other objects such as trees, birds and animals, water damage, ice and snow, fire, etc.9
Accidents caused by man-made disasters can be detected and repaired early, and distribution line accidents can be prevented, thereby improving the reliability of stable power supply. In addition, the seventh
In the figure, ■. For, Va is AC wave, distorted wave, V
r is a rectangular wave, Vs is a staircase wave, Vi is an irregular distorted wave, Vd
is the DC superimposed wave, vh is the high frequency damping frequency, and Vz is ■. Indicates the case where there is no change, and for Io, Ia is an AC wave, distorted wave, Ir is a rectangular wave, Iゎ is a needle wave, Ii is an irregular distorted wave, Ih is a high frequency damping frequency, and Iz is an I0 change. Indicates the case where there is no

[Problem to be Solved by the Invention] A conventional abnormal state monitoring device for a power distribution line is configured as described above, and detects zero-sequence voltage that occurs at a precursor stage of a failure or an instantaneous failure stage in a power distribution line. Collect the abnormal waveform of zero-sequence current, collect this abnormal waveform,
It determines which waveform classification data this abnormal waveform corresponds to, extracts the cause corresponding to the corresponding waveform classification data, and thereby predicts failures before they lead to permanent failures. , Abnormal waveforms of zero-sequence voltage and zero-sequence current collected at distribution substations are transmitted through a signal transmission path consisting of system constants such as the inductance of the distribution line and ground capacity, so the abnormal waveform of the fault point is transmitted. It is different from the abnormal waveform that occurs at the failure point. For this reason, it was difficult to correlate the waveform classification of abnormal waveforms with failure types such as defective insulators, contact with trees, and transformer accidents. As a classification of failure types, ■. , I
In both cases, there are many phenomenon items within the same frame where AC waves and distorted waves occur, making it difficult to distinguish, for example, a defective insulator. Therefore, there is a problem in that it is difficult to detect the detailed failure prediction stage. This invention was made to solve the above-mentioned problems, and by analyzing and classifying abnormal waveforms in distribution lines within slave stations, abnormalities in distribution lines can be discovered early at the failure prediction stage. The object of the present invention is to obtain an abnormal condition monitoring device for power distribution lines that prevents failures.

[Means to solve the problem]

In the power distribution line abnormal condition monitoring device according to the present invention, in order to divide the functions between the slave station and the master station, the slave station first detects the zero-sequence voltage and zero-sequence current occurring in the distribution line, and then detects the zero-sequence voltage and zero-sequence current. The abnormal waveform of the phase current is detected by the abnormal waveform detection means, the abnormal waveform detected here is analyzed by the waveform analysis means, and this waveform analysis data is registered in advance in the waveform classification memory by the waveform classification means to generate waveform classification data. The abnormal waveform is classified as a waveform, and the data is output from the slave station's modem to the master station's modem. The master station stores the abnormal waveform in the waveform classification memory, and uses the abnormality cause determination means to determine the abnormality cause corresponding to the analyzed and classified waveform data according to the verification result.
Based on the determined cause of the abnormality, the failure prediction means outputs failure prediction information for the power distribution line.

[For use]

The waveform classification means in this invention is provided in each slave station, and enables abnormal waveforms of zero-sequence voltage and zero-sequence current of the distribution line to be automatically collected by waveform classification. Further, the failure prediction means of the master station detects a failure section from the output content of the abnormality cause data determined and extracted by the abnormality cause determination means, thereby discovering an abnormality in the distribution line at an early stage at the failure prediction stage. Then, failures can be prevented before they occur, and failures can be removed and restored at an early stage.

【Example】

An embodiment of the present invention will be described below with reference to the drawings. In FIGS. 1 to 3, the same parts as in FIGS. 8 and 9 are designated by the same reference numerals. In FIGS. , ZCTn is a zero-phase current detector provided in the slave station, ZVn is a zero-phase voltage detector,
30A and 30B are modems for communication between the master station 40 and the slave station n, RAM3 is a temporary storage memory and is a waveform classification data memory of the slave station, and ROM2 is a read-only memory and is a cause-specific data memory. Next, the operation will be explained. First, in this invention, the functional operations such as detection and waveform analysis, which were conventionally processed collectively in the master station 40, are divided between the master station 40 and the slave station n, and abnormal waveforms are analyzed within the most efficient range of each other. Classify and extract causes. For example, the master station 40 is connected to the respective slave stations 11 and 1.
2...n, information is collected periodically via the communication line C by a polling method in order to monitor the presence or absence of system voltage, the opening/closing status of switches, etc. At that time, the zero-sequence voltage and zero-sequence current detection means ZVn of the slave station n installed on the distribution line,
When an abnormal waveform is detected by the ZCTn 20, this abnormal waveform is converted into a signal by the signal conversion means 21, and the abnormal waveform is converted into a signal by the abnormal waveform detection means 22.
Therefore, the detected abnormal waveform is analyzed by the waveform analysis means 23, and the next waveform classification means 24 compares it with the waveform classification data registered in the waveform classification memory 25 in advance.
. A peculiar waveform number is assigned to the I0 abnormal waveform data and the abnormal waveform analysis data (Fig. 6, step 5T16), the above is processed by the slave station n, and the modem 30A of the master station 40 is sent from the modem 30B to the modem 30A of the master station 40.
send a signal to At the master station 40, the transferred data is
The cause corresponding to the waveform classification number stored in AM is extracted by the abnormality cause determination means 26 from the cause data stored in the cause data memory ROM, +. . As a result, each slave station detects an abnormality in the distribution line early at the stage of the failure prediction means 27, detects it only when it is necessary to detect a faulty section, and then moves on to the operation of removing the faulty part and restoring it. .

【Effect of the invention】

As described above, according to the present invention, the functions are shared between the master station and the slave station, and the slave station handles the zero-sequence voltage generated in the distribution line,
An abnormal waveform of the zero-sequence current is detected by an abnormal waveform detection means, the detected abnormal waveform is analyzed by a waveform analysis means, and the analyzed waveform analysis data is compared with waveform classification data registered in advance in a waveform classification means. According to the comparison result, a waveform classification number is assigned to the abnormal waveform and stored in the memory, and the data is sent to the master station via the communication line. The master station uses the abnormality cause determination means to determine the abnormality cause corresponding to the analyzed and classified waveform data, and based on the determined abnormality cause, the failure prediction means predicts a failure in the distribution line and detects a fault section. As a result, it is now possible to automatically accumulate data for analyzing and classifying abnormal waveforms of V, , and Io that occur in distribution lines at each slave station level, and to check the correlation between abnormal waveforms and distribution line failures. The accuracy of judgment is greatly improved as it is less affected by the system constants of the distribution system, and since the master station mainly predicts distribution line failures, early detection and improved reliability can be achieved. Also ■. By analyzing and comparing the waveforms of Io and Io, it is possible to discover distribution line failures at their precursor stage, and this discovery makes it easier to carry out patrol inspections of abnormal lines and their specific equipment. Therefore, it is possible to repair deteriorated or damaged parts before they lead to permanent failure. As a result, the failure location can be removed and restored quickly, and the time required for power outages due to distribution line failures can be shortened.

[Brief explanation of drawings]

FIG. 1 is a block diagram of a fault section detection system according to an embodiment of the present invention, FIG. 2 is a block diagram showing a functional division configuration between a master station and a slave station according to the present invention, and FIG. 3 is a distribution line abnormality according to the present invention. FIG. 4 is a functional operation block diagram of the condition monitoring device.
The figure is a functional operation block diagram of a conventional distribution line abnormal state monitoring device, FIG. 6 is a flowchart showing the detailed operation sequence of FIG. 5, and FIG. , Io waveform diagram showing waveform classification data, FIG. 8 is ■. , Io is an abnormality cause diagram corresponding to waveform classification data. In the figure, 20 is zero-sequence voltage and zero-sequence current detection means;
1 is a signal conversion means, 22 is an abnormal waveform detection means, 23 is a waveform analysis means, 24 is a waveform classification means, 25 is a waveform classification memory, 26 is an abnormality cause determination means, 27 is a failure prediction means, 3
0A and 30B are modems, 40 is a master station, and n is a slave station. In addition, in the figures, the same reference numerals indicate the same or equivalent parts. Patent Applicant: Mitsubishi Electric Corporation, Figure 1, Figure W (Y-1) (a) Figure W (-f-2) (b) Procedural amendment (voluntary)

Claims (1)

[Claims] A plurality of slave stations installed at locations where switches are installed that separate distribution lines connected to a distribution substation, and a parent station that receives failure detection information of the distribution line detected by the slave stations and controls the switches. a station, zero-sequence voltage and zero-sequence current detection means for detecting zero-sequence voltage and zero-sequence current occurring in the distribution line, and sampling and converting the zero-sequence voltage and zero-sequence current from the detection means into digital data. abnormal waveform detection means for detecting abnormal waveforms of zero-sequence voltage and zero-sequence current using digital data from the signal conversion means; and abnormal waveform detection means for detecting abnormal waveforms of zero-sequence voltage and zero-sequence current. a waveform analysis means of the slave station that analyzes the abnormal waveform detected by the slave station; a waveform classification means of the slave station that classifies the waveform by comparing the waveform analysis data analyzed by the waveform analysis means with pre-registered waveform classification data; a waveform classification memory of the slave station that stores abnormal waveforms classified by the waveform classification means; a modem that connects the slave station and the master station via a communication line; an abnormality cause determining means of the master station that determines the cause of the abnormality based on the abnormality cause data registered in the above and the abnormal waveform; and a master station that predicts failure of the distribution line based on the abnormality cause determined by the abnormality cause determination means. An abnormal state monitoring device for a power distribution line, which is equipped with a failure prediction means.