CN112926750A - Intelligent matching method and device for fault characteristic values of multiple power monitoring points - Google Patents
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Abstract
The invention relates to an intelligent matching method and device for fault characteristic values of multiple monitoring points of electric power, which comprises the following steps: step 1) a power failure characteristic value storage process, establishing a characteristic packet through historical data, selecting corresponding alarm information, locking monitoring point information, and associating a knowledge base; and 2) in the power failure characteristic value matching process, comparing the real-time data with the data in the characteristic packet, and generating an alarm when the remote signaling data and the remote measuring data respectively meet the matching rules. Compared with the prior art, the method has the advantages of solving the problem that the single alarm cannot accurately position the fault and the like.
Description
Technical Field
The invention relates to the technical field of power system fault maintenance, in particular to an intelligent matching method and device for fault characteristic values of multiple power monitoring points.
Background
An scada (supervisory Control And Data acquisition) system, i.e. a Data acquisition And monitoring Control system. The SCADA system is a DCS and electric power automatic monitoring system based on a computer; the method has wide application field, and can be applied to a plurality of fields such as data acquisition and monitoring control, process control and the like in the fields of electric power, metallurgy, petroleum, chemical industry, gas, railways and the like.
At present, after a work order is generated in a power company system, a maintenance worker manually selects a knowledge base according to a fault phenomenon, but the same or similar fault phenomena have a plurality of knowledge bases, and the maintenance worker has no way to know which knowledge base to use? Often, the knowledge base is not selected or the wrong knowledge base is selected, so that the overhaul task is difficult to complete, and further the working efficiency of a company is influenced.
Chinese patent publication No. CN 108054734A is retrieved, and discloses a distribution network protection method and system based on fault feature matching, and the method specifically comprises the following steps: the method comprises the following steps that firstly, when a power distribution network fails, current fault characteristic values of all positions in the power distribution network are obtained in real time; matching the current fault characteristic values of all positions in the power distribution network with reference fault characteristic values corresponding to each fault type prestored in a fault type database to obtain a fault type corresponding to the current fault; thirdly, inquiring a protection strategy corresponding to the fault type in a protection strategy database according to the fault type; and step four, forming a protection action according to the inquired protection strategy, and executing the protection action to protect the power distribution network with the fault. However, when the power system fails, a batch of monitoring points often alarm at the same time, and the alarm processing efficiency in the prior art is low one by one and is easy to misjudge.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an intelligent matching method and device for fault characteristic values of multiple power monitoring points.
The purpose of the invention can be realized by the following technical scheme:
according to one aspect of the invention, an intelligent matching method for fault characteristic values of power multiple monitoring points is provided, which comprises the following steps:
step 1) a power failure characteristic value storage process, establishing a characteristic packet through historical data, selecting corresponding alarm information, locking monitoring point information, and associating a knowledge base;
and 2) in the power failure characteristic value matching process, comparing the real-time data with the data in the characteristic packet, and generating an alarm when the remote signaling data and the remote measuring data respectively meet the matching rules.
As a preferred technical solution, the power failure characteristic value warehousing process specifically includes:
step 101) selecting an alarm;
step 102) searching monitoring points;
step 103) hanging a knowledge base;
step 104) remote signaling and telemetry processing;
step 105) warehousing.
As a preferred technical solution, the step 101) of selecting an alarm specifically includes:
dragging a time axis, and dynamically displaying sites with alarms in the time period and the alarm number of the sites; all sites are selected by default, some sites can be removed, and the alarm graph changes dynamically as the number of the sites increases.
As an optimal technical scheme, the time axis can simultaneously display a high-precision time axis and a low-precision time axis through dragging, and the distribution condition of the alarm monitoring points in the selected time period is synchronously displayed.
As a preferred technical solution, the step 102) of searching for the monitoring point specifically includes:
after the alarm is selected, monitoring points are searched according to the alarm data and are brought into a fault packet; monitoring points which are not alarmed but marked as more important can be added;
for telemetry information, the alarm will distinguish between a severe violation or a minor violation.
As a preferred technical solution, the hooking knowledge base in the step 103) is specifically:
the captured data is a sample data packet which can be hung to an existing knowledge base or a newly-built knowledge base.
As a preferred technical solution, the step 104) of remote signaling and telemetry processing specifically includes: the characteristic value of the remote signaling data is a remote signaling value; the telemetry data is algorithmically calculated for slope.
As a preferred technical solution, the warehousing in step 105) is specifically as follows: and writing the remote signaling data, the remote measuring data and the knowledge base in the characteristic packet into the characteristic value sample base.
As a preferred technical solution, the matching process of the power failure characteristic value in step 2) is specifically as follows:
when external data come temporarily, a corresponding matching rule is completed, and then fault diagnosis and alarm are carried out, wherein the matching rule specifically comprises the following steps:
matching rule 1: only remote signaling data exists in the feature packet, and the matching degree > is 80 percent, which is defined as matching;
matching rule 2: only telemetering data exists in the feature packet, and the matching degree > is 80%, the matching is defined as up;
matching rule 3: the characteristic packet contains telemetering and remote signaling, the weight of the telemetering and remote signaling is 1/2 respectively, and the matching degree after comprehensive calculation is 80, which is defined as matching;
matching rule 4: the feature packet assumes that there are 10 sample data, and when any eight sample data are matched, the matching degree rule is calculated to be satisfied;
matching rule 5: taking the data of 1 day as a sample, completing the rule with the matching degree of 80%, matching the fault, and completing fault diagnosis;
matching rule 6: and (3) judging whether the growth rate of the single telemetering data characteristic value matching rule is positive or negative, and judging that the single growth rate is matched, wherein the following conditions are met:
matching rule 7: the absolute value of the growth rate is more than or equal to 90% of the absolute value of the growth rate of the sample characteristic value;
matching rule 8: the sign of the growth rate is consistent with the sign of the sample characteristic value.
According to another aspect of the invention, an intelligent matching device for fault characteristic values of power multiple monitoring points is provided, which comprises:
the power failure characteristic value storage module is used for establishing a characteristic packet through historical data, selecting corresponding alarm information, locking monitoring point information and associating a knowledge base;
and the power failure characteristic value matching module is used for comparing the real-time data with the data in the characteristic packet and generating an alarm when the remote signaling data and the remote measuring data respectively meet the matching rules.
Compared with the prior art, the invention extracts a group of fault information into the characteristic value, and puts the characteristic value and a corresponding solution into the knowledge base as a fact storage basis, solves the problem that a single alarm cannot accurately position the fault by utilizing an intelligent maintenance strategy, and replaces the work task of maintenance personnel to a certain extent so as to solve the problem that the old large-scale information system fault maintenance is completed only by manpower and experience.
Drawings
FIG. 1 is a block diagram of a power failure signature matching method of the present invention;
FIG. 2 is a flow chart of a power failure eigenvalue matching method of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
As shown in fig. 1, the intelligent matching method for fault characteristic values of multiple monitoring points of electric power of the invention is based on technologies such as SCADA system and big data application, and the method comprises the following steps: SCADA data of the power equipment can be transmitted continuously, and when the platform detects that the data exceeds a threshold value, an alarm can be generated. And establishing a feature packet, selecting corresponding alarm information, locking monitoring point information, and associating a knowledge base.
And when the subsequent SCADA data is transmitted, comparing the data with the data in the feature packet, and when the remote signaling data and the remote measuring data respectively meet the matching rules, outputting an alarm and automatically giving a solution.
The invention relates to a power failure characteristic value storage method;
step 1: selecting an alarm, wherein the specific method comprises the following steps:
dragging the time period, and dynamically displaying the sites with alarms in the time period and the alarm number of the sites;
all sites are selected by default, some sites can be removed, and the alarm graph changes dynamically;
the time axis can be dragged, and a high-precision time axis and a low-precision time axis can be displayed at the same time;
and synchronously displaying the distribution condition of the alarm monitoring points in the selected time period.
Step 2: the monitoring point is searched, and the specific method comprises the following steps:
and after the alarm is selected, searching monitoring points according to the alarm data, and bringing the monitoring points into the fault packet.
Monitoring points which are not alarmed but are regarded as important can be added.
For telemetry, the alarm will distinguish between a severe over-limit (above a set high threshold) or a slight over-limit (above a set low threshold).
And step 3: the specific method for hanging the knowledge base comprises the following steps:
the captured data is a sample data packet which can be linked to an existing knowledge base or a newly-built knowledge base.
And 4, step 4: the remote signaling and remote measuring process includes the following steps:
the characteristic value of the remote signaling data is a remote signaling value;
the characteristic value of the telemetering data is an increase rate, namely sample calculation of the characteristic packet is included, and the increase rate is (alarm time point value-one point value before the alarm time)/one point value before the alarm time;
if the growth rate is positive or negative, judging that the single growth rate is matched, and simultaneously satisfying the following conditions:
1. the absolute value of the growth rate is more than or equal to 90% of the absolute value of the growth rate of the sample characteristic value;
2. the sign of the growth rate is consistent with the sign of the sample characteristic value.
And 5: warehousing, wherein the specific method comprises the following steps:
writing the remote signaling data, the remote measuring data and the knowledge base in the feature packet into the feature value sample base
And when external data come temporarily and the corresponding matching rule is completed, performing fault diagnosis and alarm.
FIG. 2 is a matching method of characteristic values of power failure of the present invention:
matching rule 1: only remote signaling data exists in the feature packet, and the matching degree > is 80 percent, which is defined as matching;
matching rule 2: only telemetering data exists in the feature packet, and the matching degree > is 80%, the matching is defined as up; the sample value of the content of the telemetering data can be expressed in various forms and is temporarily set as the growth rate;
matching rule 3: the characteristic packet contains telemetering and remote signaling, the weight of the telemetering and remote signaling is 1/2 respectively, and the matching degree after comprehensive calculation is 80, which is defined as matching;
matching rule 4: the feature pack assumes that there are 10 sample data (a1, a 2.., a10), and when any eight sample data are matched, the matching degree rule is calculated to be satisfied;
matching rule 5: taking the data of 1 day as a sample, completing the rule with the matching degree of 80%, matching the fault, and completing fault diagnosis;
matching rule 6: and (3) judging whether the growth rate of the single telemetering data characteristic value matching rule is positive or negative, and judging that the single growth rate is matched, wherein the following conditions are met:
matching rule 7: the absolute value of the growth rate is more than or equal to 90% of the absolute value of the growth rate of the sample characteristic value;
matching rule 8: the sign of the growth rate is consistent with the sign of the sample characteristic value.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The intelligent matching method for the fault characteristic values of the power multi-monitoring point is characterized by comprising the following steps of:
step 1) a power failure characteristic value storage process, establishing a characteristic packet through historical data, selecting corresponding alarm information, locking monitoring point information, and associating a knowledge base;
and 2) in the power failure characteristic value matching process, comparing the real-time data with the data in the characteristic packet, and generating an alarm when the remote signaling data and the remote measuring data respectively meet the matching rules.
2. The intelligent matching method for the fault characteristic values of the power multiple monitoring points according to claim 1, wherein the warehousing process of the fault characteristic values of the power specifically comprises the following steps:
step 101) selecting an alarm;
step 102) searching monitoring points;
step 103) hanging a knowledge base;
step 104) remote signaling and telemetry processing;
step 105) warehousing.
3. The intelligent matching method for the fault characteristic values of the power multiple monitoring points as claimed in claim 2, wherein the step 101) of selecting alarm specifically comprises the following steps:
dragging a time axis, and dynamically displaying sites with alarms in the time period and the alarm number of the sites; all sites are selected by default, some sites can be removed, and the alarm graph changes dynamically as the number of the sites increases.
4. The intelligent matching method for the fault characteristic values of the power multiple monitoring points as claimed in claim 3, wherein the time axis can simultaneously display a high-precision time axis and a low-precision time axis by dragging, and synchronously display the distribution conditions of the alarm monitoring points in the selected time period.
5. The intelligent matching method for the fault characteristic values of the multiple power monitoring points according to claim 2, wherein the step 102) of searching the monitoring points specifically comprises the following steps:
after the alarm is selected, monitoring points are searched according to the alarm data and are brought into a fault packet; monitoring points which are not alarmed but marked as more important can be added;
for telemetry information, the alarm will distinguish between a severe violation or a minor violation.
6. The intelligent matching method for the fault characteristic values of the power multiple monitoring points according to claim 2, wherein the step 103) of hooking the knowledge base specifically comprises the following steps:
the captured data is a sample data packet which can be hung to an existing knowledge base or a newly-built knowledge base.
7. The intelligent matching method for the fault characteristic values of the power multiple monitoring points according to claim 2, wherein the step 104) of remote signaling and remote measuring is specifically as follows: the characteristic value of the remote signaling data is a remote signaling value; the telemetry data is algorithmically calculated for slope.
8. The intelligent matching method for the fault characteristic values of the power multiple monitoring points as claimed in claim 2, wherein the step 105) of warehousing specifically comprises the following steps: and writing the remote signaling data, the remote measuring data and the knowledge base in the characteristic packet into the characteristic value sample base.
9. The intelligent matching method for the fault characteristic values of the power multiple monitoring points as claimed in claim 2, wherein the matching process for the fault characteristic values of the power in the step 2) is specifically as follows:
when external data come temporarily, a corresponding matching rule is completed, and then fault diagnosis and alarm are carried out, wherein the matching rule specifically comprises the following steps:
matching rule 1: only remote signaling data exists in the feature packet, and the matching degree > is 80 percent, which is defined as matching;
matching rule 2: only telemetering data exists in the feature packet, and the matching degree > is 80%, the matching is defined as up;
matching rule 3: the characteristic packet contains telemetering and remote signaling, the weight of the telemetering and remote signaling is 1/2 respectively, and the matching degree after comprehensive calculation is 80, which is defined as matching;
matching rule 4: the feature packet assumes that there are 10 sample data, and when any eight sample data are matched, the matching degree rule is calculated to be satisfied;
matching rule 5: taking the data of 1 day as a sample, completing the rule with the matching degree of 80%, matching the fault, and completing fault diagnosis;
matching rule 6: and (3) judging whether the growth rate of the single telemetering data characteristic value matching rule is positive or negative, and judging that the single growth rate is matched, wherein the following conditions are met:
matching rule 7: the absolute value of the growth rate is more than or equal to 90% of the absolute value of the growth rate of the sample characteristic value;
matching rule 8: the sign of the growth rate is consistent with the sign of the sample characteristic value.
10. The utility model provides a many monitoring points of electric power fault eigenvalue intelligence matching device which characterized in that includes:
the power failure characteristic value storage module is used for establishing a characteristic packet through historical data, selecting corresponding alarm information, locking monitoring point information and associating a knowledge base;
and the power failure characteristic value matching module is used for comparing the real-time data with the data in the characteristic packet and generating an alarm when the remote signaling data and the remote measuring data respectively meet the matching rules.
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| CN110826735A (en) * | 2019-10-31 | 2020-02-21 | 上海玖道信息科技股份有限公司 | Electric power SCADA intelligent multidimensional query and maintenance method |
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| 邹继行: ""风电场群集控中心SCADA系统的设计与开发"", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
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Application publication date: 20210608 |