JPH01160320A - Electric power system fault judging device - Google Patents

Abstract

PURPOSE:To enable verify work such as checking of an inference system through utilization of an external information, by providing an external file and an input machine thereby enabling input of information subjected to verify work therefrom. CONSTITUTION:When a state change on a power system is set in a system state change 1, an inference engine 22 in a power system fault judging device 2 is initiated to start. Then inference is proceeded by means of the inference engine 22 according to the control knowledge in a knowledge base 21. Consequently, knowledge applying condition in inference process is stored in inference information and a judgement result 3 of operation principle judging process is outputted. When a case of fault to be verified is specified at a verification specify 4, a verify mechanism 24 is started. The verify mechanism 24 obtains verify data from an inference information storing file 6 and an inference information input 7 while extracting an identifier for the specified fault case from inference information 23 and subtracts a work sequence of knowledge guidance from a detection knowledge base 25, then a work defined in the knowledge base 25 is performed.

Description

[Detailed Description of the Invention] [Object of the Invention] (Industrial Application Field) The present invention is a power system monitoring and control system that automatically determines the accident status of a power system based on information observed from the power system. installed in the power system fault determination device.

(Prior art) Conventionally, when attempting to automatically determine accidents in an electric power system, the logic for accident determination was written in an existing language (Fortra).
n, etc.) and is built into a computer, and there has been no one that has realized the function of verifying the determination results.

(Problem to be solved by the invention) When automatically determining fault points in an electric power system, if only the determination results are output, it is difficult to understand why such a result was obtained or the reason for the determination. , it is necessary to perform verification using inference information at the time of judgment.

In this case, the subject of verification is the inference information stored in the judgment system at the time of verification, and if it is not possible to import inference information from the outside, the target of verification is the inference information stored in the judgment system at the time of verification, and if it is not possible to import inference information from the outside, Limited to inference information regarding judgment.

Therefore, the judgment is whether the inference is correct or not! It is not possible to register data that can serve as an Ir standard in advance in an external file, etc., and import it for comparison and consideration during verification.

The present invention makes it possible to input inference information to be verified from the outside when verifying the determination result (2) when determining an actual power system accident or simulating a hypothetical accident. The purpose of this research is to provide a power system fault determination device that can perform various verification tasks.

[Structure of the Invention] (Means for Solving Problems) The present invention includes a knowledge base 21 that stores knowledge used to determine fault points in an electric power system in the form of rules, and a knowledge base 21 that stores knowledge in the form of rules. In the power system accident determination device 2 equipped with an inference engine 22 that performs inference processing by selecting and combining them, the state of knowledge application in the inference process of the knowledge base by the inference engine is saved, and the saved content is used to calculate the decision result. When performing the verification, external files and input devices were provided so that the information subject to the verification work could be input from these as well.

(Function) When an accident is determined by the power system accident determination device 2 shown in FIG. Based on this, the inference engine 22 is used to select and combine knowledge in the knowledge base 21 to perform inference. The knowledge application status in this inference process is stored in the inference information 23 in parallel with the inference. The inference result is then output as determination result 3.

When a verification work request is issued to the verification mechanism 24 from the verification designation 4, verification is performed using the inference information 23, but if necessary, the inference information storage file 6, the inference information person's cuff, etc. are used as verification data. The content of the knowledge base 21 is imported and verification is performed while providing guidance for the verification work using the verification knowledge base 25. These verification work results are output as verification results 5.

In the inference information storage file 6, the verification mechanism 24 can store the data of the inference information 23 as is or after processing.

Therefore, inference information from the outside can be input via the inference information storage file.

(Example) Examples will be described below with reference to the drawings.

FIG. 1 is a functional block diagram of an embodiment of the power system fault determination device according to the present invention.

In FIG. 1, reference numeral 1 indicates information on a change in the system state, and using this as a trigger, the power system fault determination device 2 operates and outputs a determination result 3.

The verification designation 4 activates the verification function of the judgment result and causes the verification result 5 to output the verification content. The inference information storage file 6 is an external storage file for verification data, and the inference information person cuff is an input of inference information at the time of verification.

The power system accident determination device 2 includes a knowledge base 21 that stores knowledge for determining accidents in the power system in the form of rules;
An inference engine 22 that performs inference by selecting and combining knowledge from a knowledge base, inference information 23 that stores knowledge application status in the inference process, a verification mechanism 24 that performs various verification tasks, and a verification mechanism 24 that stores knowledge for verification tasks. It is composed of a verification knowledge base 25.

Figure 2 is a side view of the power system, and the following accident situation will be explained based on this. Figure 2 has a parallel two-line configuration connected to the power supply, and a shear disconnector (CB1.C
B2) is largely cut off by each main protection relay (RYl, RY2).

FIG. 3 is a side view of the configuration for explaining the operation of the power system fault determination device 2 at the time of fault determination. Systematic variation 1 shown here includes 1. The state changes (operating relay names and 8 circuit breakers C) in the system example shown in FIG. 2 are set.

The knowledge base 21 in this case is shown in FIG.
2, the configuration of which is roughly shown in FIG. The inference information 23 stores the inference process and judgment results as described above, and examples of inference information include 1nf(t, operation relay (RY
l, RY2)> will be explained below.

t in this description example is an identifier of inference information,
This allows us to recognize a set of inference information for one systematic variation. “Operation relay (RYl, RY2)° is information at the time of inference.

From the above contents, to explain the above inference information example, "
This means that there is ``operational relay (RYI, RY2)'' as inference information regarding the systematic change recognized by the identifier.

The verification mechanism 24 performs verification work according to a verification instruction specified by a verification designation (described later) 4 in order to perform verification.

Determination result 3 shows the accident determination result inferred by power system accident determination device 2 in response to the situation set in system state change 1.

In this case, since the judgment result is regarding the accident information shown in Fig. 2, the operating relays are RYl and RY2, and the
Container CB1. Since CB2 was activated, alpha ray 1 [
There is a possibility of an accident.

Verification designation 4 is used to activate the verification function for confirming (verifying) the inference process again for accident cases that have already been determined by the power system accident determination device 2. Specify selection and verification tasks.

Verification result 5 shows the verification result for the accident case specified in verification designation 4.

FIG. 4 is a configuration diagram of the knowledge base, and for example, the knowledge shown in the figure is an example of knowledge. Each knowledge will be explained below.

m control knowledge The following knowledge will be explained as an example of control knowledge.

Control knowledge (operating principle, 1.1nf2, [operating relay],
[Simple accident]).

In the above knowledge description, the ``operating principle'' is judgment knowledge 2.
12 judgment knowledge names, 1' is the application order of the judgment knowledge ``operation principle'' at the time of inference, '1nf2° is the inference method in the ``operation principle'' module (described later), and ``[operation relay]'' is the ``operation principle''. The input value "[simple accident]" when applying principle knowledge is the same output value. Therefore, the above knowledge example is based on "the judgment knowledge of "operating principle" is adopted as the first step when inferring the system fault point. , the inference method used in this case is "1nf2° (search for preferential reflections and apply one)".

The input to the ``operating principle'' is an ``operating relay'', and the output is a ``simple accident.'' ”, which means that P
It is written in ROLOG language.

(ii) Judgment Knowledge The judgment knowledge 212 includes four judgment knowledge modules: ``Principle of Operation'', ``Multiple Accidents'', ``Malfunction Accident'', and ``Malfunction Accident''. Here, ``principle of operation'' refers to the knowledge of extracting accident candidate sections from the operating principle of relays, and ``multiple accidents'' refers to the knowledge of extracting the possibility of multiple accidents occurring at the same time from the accident candidate section. Operational accidents are the knowledge to judge accidents that are caused by the malfunction of relays and circuit breakers, and ``malfunction accidents'' are the knowledge to judge accidents that are caused by the malfunction of equipment. An example of knowledge is shown below.

Operating principle (-operating relay, - simple accident) knee po (-priority 1), Pl (-operating relay, - disconnection CB), P2 (-1, Ya disconnection CB, one section), P3 (one section , - simple accident).

To explain the above knowledge, first, '-operation-°' is the input value, and '=simple accident' is the output value.

"PO°~"P3' are basic knowledge defined in the basic matter 213, "PO(-priority 1)' indicates that the priority of this knowledge is 1, and °P1(-operation relay ,
-Cut ce)' indicates that the CB cut off by the activated relay is -Cut CB, and 'P2(-
t, or disconnection CB, one section) ° indicates that the load-side equipment of the cut-off CB is in one section, and P3 (one section, - simple accident) ° indicates that the power outage is in one section. Indicates an accident. This means that "among the load-side equipment of a CB that has been cut off by a certain operating relay, the equipment that is out of power is in the simple fault section (priority = 1)" and is written in the PROLOG language. are doing.

(iii) Basic matters Examples of basic knowledge are shown and explained below.

PO(X,X) In the above knowledge description, it is shown that the first variable X given to PO and the second variable X are equivalent. This means that the first variable is bound to the second variable, and that it is checked whether the value of the first variable and the value of the second variable are equal.

In the former case, use something like ``PO(-priority, 2)°; in the latter case, assuming some value is given to A and B, use the form ``PO(A, B)''. This basic information is also described in the PROLOG@ story.

(iv) System data The system data 214 defines data necessary for accident determination, such as the connection status of the system and the charging/power outage status of equipment.

An example of systematic data is shown below.

System equipment (alpha line 1 [, power transmission lines, power outage).

To explain the above knowledge, System equipment is an identifier that expresses the relationship and attributes of the data to be defined, and the data related to the system equipment is collectively defined in parentheses that follow.

Here, the system equipment is defined as equipment name "α line and ', equipment type: power transmission line", and equipment charging/outage status "power outage°". An example of this knowledge is "transmission line, alpha line 1 [is It means that there is a power outage] and is written in the PROLOG language.

FIG. 5 is a diagram showing an example of the configuration of the inference engine. In this example, there are three inference methods. . “Total exploration is a method of searching knowledge and extracting all that is applicable. Priority ordering is a method of searching knowledge in order of priority (the smaller the number, the higher the priority), This is a method where the inference ends when one applicable item is extracted, and the ``order on the knowledge base'' means searching in the order in which they are listed on the knowledge base and extracting one applicable item. If so, the inference ends there.

FIG. 6 shows a configuration example of the verification knowledge base 25, and the knowledge example will be explained. Verification knowledge includes knowledge that defines the procedure of verification work and knowledge that defines each operation in verification work. The knowledge that defines the procedures for verification work is guidance (verification level, work procedure).

It is expressed as. Here, the verification level is the purpose and level of the user who is trying to verify (for example, how much of the details of the accident do you want to know about the accident case that is the subject of verification?), and the work procedure is the purpose and level of the user who is trying to verify. The work contents are shown in the order of verification operations described below. The definition of the verification work is defined in the form of a PROLOG grogram, such as: Work x Knee:

for example, Guidance (simply confirming the a-theory process, [Task 1]).

For users who only want to know the details of the inference process,
It shows that only work 1 needs to be performed, and in work 1, the operation of converting inference information into text and showing the inference process is defined by the PROLOG program.

Guidance (I don't know the verification method,
Task 2, Task 3, Task 4], the user who does not know the verification method can perform each verification task defined as a verification task, that is, task 1 of converting and outputting the inference process into text.
, work 2 for checking accident situation settings, work 3 for printing a list of system data, and work 4 for individually checking system data.

Note that in each work, the above-mentioned operations are defined by a PROLOG program.

FIG. 7 shows an example of the configuration of the inference information storage file 6. This is a file in which inference information is stored, and its contents may be the inference information 23 as it is or may be stored after being processed.

1nf(j,...).

is an example where it is stored as is, and 1nf (in, ・
・・）.

is an example in which information is processed and stored.

1nf (ni, . . . ) is an example in which information is summarized for each module of judgment knowledge.

FIG. 8 is a display example of the inference information person's cuff. The contents of the system information are displayed and data for the inference process is input. The underlined portion in FIG. 8 is the input request. These input values are put together to create inference information.

Next, the effect will be explained.

First, when determining an accident regarding the system status shown in Fig. 2 using the configuration shown in Figs. 3, 4, and 5,
When the state change on the power grid is set to grid state change 1,
For the inference engine 22 of the power system accident determination device 2,
The start of the judgment is activated. In response to this, in accordance with the control knowledge in the knowledge base 21, inference is proceeded using the inference engine 22 in the order of operating principle -> malfunction/non-operation accident -> multiple accidents -> malfunction accident. The knowledge application status in these reasoning processes is stored in the reasoning information 23. For example, an example of storing the reasoning information when determining the operating principle is shown below.

In the process of determining the operating principle, each operating relay (RYI,
The application result of the judgment knowledge 212 for RY2) is stored as the following information.

1nf(t), operating principle (RYl, (2 wires and)).

1nf (t, operating principle (RY2. CI line 11)).

Then, the overall result of the operation principle judgment is expressed as 1nf(t
, operating principle (alpha ray H)).

These are stored as judgment results 3 and output as shown in FIG.

In addition, in the case of an accident determination based on system status change 1, the verification mechanism 24, verification designation 4, verification result 5, inference information storage file 6, inference information person cuff, and verification knowledge base 25 do not operate.

After determining the accident based on the actions described above, the determination results are verified.

FIG. 9 is a flowchart showing the processing details at the time of verification. First, specify the accident case for verification purpose in verification designation 4,
The verification mechanism 24 of the power system fault determination device 2 is activated. In this case, the verification mechanism 24 extracts inference information having the identifier of the accident case specified by the verification specification 4 from the inference information 23 (step 591).

The inference information 23 includes inference information related to one or more cases of accident determination, and the verification mechanism 24 searches for one whose identifier specified in the verification specification 4 matches the first term of the inference information inf. and is extracted (step 593).

If you wish to use the data stored in the inference information storage file 6, specify the file name in the verification specification 4 (step 592) and read it into the verification@structure 24 (step 595). If a human wants to directly input verification data, he or she specifies inference information input in the verification designation and inputs it to the verification mechanism 24 using the inference information person cuff (step 594).

Once the verification data has been prepared as described above, the verification work is performed using the verification knowledge base 25 while providing guidance for the verification work (step 896).

The results of the verification work are displayed in verification results 5 (step 597).

The data of the inference information 23 is directly stored in the inference information storage file 6 specified by the verification specification 4 by the verification mechanism 24.
Or it can be processed and stored.

In the case of verification, systematic state variation 1, inference engine 22, and determination result 3 do not work.

According to this embodiment, it is possible to check the inference system using comparison with the basic inference pattern. A specific example will be shown below using the flowchart shown in FIG.

When making inferences with the power system fault determination device 2, the power system state change 1
As a result, a basic accident in the system is generated in a pseudo manner,
The inference information 23 is stored as a basic inference pattern in the inference information storage file 6 using the verification mechanism 24.

If you want to check whether the correct inference has been made when the knowledge in the knowledge base 21 has been modified, etc., use the electric power system accident determination device 2 to simulate a basic accident, perform the inference, and check the inference information. 23 is designated from verification specification 4 and read into the verification mechanism 24 (step 810
1).

Furthermore, the information stored in the inference information storage file 6 as a basic inference pattern is read into the verification fi structure 24 (
Step 5102), by comparing and examining the basic inference pattern for the same accident situation and the inference to be checked using the verification knowledge base 25 (Stella 7810
3) Be able to check inference systems.

As a result, if they match, a good result is output in step 5104, and if they do not match, a bad result is output in step 8105.

This will be explained using FIGS. 3, 6, 7, and 8.

(1) When the basic inference pattern in the inference information storage file 6 matches the inference to be checked (FIG. 3) Inference information with identifier=t is read from the inference information 23 into the verification mechanism 24 according to the verification specification 4.

・(Figure 7) Inference information storage file 6 due to verification specification 4
is specified, and the inference information is read into the verification mechanism 24.

- Compare and examine the inference information of identifier = t and identifier = j using the guidance knowledge "inference system check" (FIG. 6) of the verification knowledge base 25. The verification work that follows is shown below.

(2) If the basic inference pattern in the inference information storage file 6 does not match the inference you want to check, change the contents of the inference information 23 in FIG. 3 as follows.

1nf (t', operating relay (RYl, RY2)).

1nf (t', L-cut CB (CBI, CB2))
.

1nf(t', operating principle (RYl, ((Z line and, α
Line 21))).

1nf(t', operating principle (RY2.(cz line and))).

1nf (t', operating principle (α-ray IL)).

1 nt (t', determination result (α-ray IL)).

At this time, a check is performed in the same manner as in (1) using the basic inference pattern shown in FIG.

(3) When inputting and checking basic inference patterns from the inference information input cuff If you want to check the inference system for systematic changes that are not registered as basic inference patterns, enter the inference information Enter the basic inference pattern using , and perform a comparison check.

However, as in cases (1) and (2), even if the basic inference pattern exists in the inference information storage file 6, it is possible that the basic inference pattern is input from the inference information person's cuff.

[Effects of the Invention] As explained above, according to the present invention, inference information is read from the outside when verifying the inference content regarding accident determination in the power system accident determination device. The information can be used to perform various verification tasks such as checking inference systems.

[Brief explanation of the drawing]

FIG. 1 is a functional block diagram of an embodiment of the power system accident determination device according to the present invention, FIG. 2 is an example diagram of the power system, and FIG. 3 is a configuration diagram of the power system accident determination device at the time of accident determination according to the embodiment. Figure 4 is a configuration diagram of the knowledge base, Figure 5 is a configuration diagram of the inference engine of the embodiment, Figure 6 is a configuration diagram of the verification knowledge base, and Figure 7 is a configuration diagram of the knowledge base.
The figure shows the configuration of the inference information storage file, Figure 8 shows an example display of inference information input, Figure 9 is a flowchart showing the processing content during verification, and Figure 10 shows the processing content when checking the inference system. FIG.

Claims (1)

[Claims] An electric power system accident determination device comprising a knowledge base that stores knowledge in the form of rules for determining failure points in an electric power system, and an inference engine that performs inference processing by selecting and combining knowledge from the knowledge base. , the state of knowledge application in the inference process by the inference engine is saved, and when verifying the judgment results using the saved contents, external files and input devices are provided and information that is the subject of verification work can be obtained from these as well. An electric power system accident determination device characterized in that it is capable of inputting information.