CN113483849A - Dynamic monitoring method for liquid level of transformer - Google Patents
Dynamic monitoring method for liquid level of transformer Download PDFInfo
- Publication number
- CN113483849A CN113483849A CN202110747318.6A CN202110747318A CN113483849A CN 113483849 A CN113483849 A CN 113483849A CN 202110747318 A CN202110747318 A CN 202110747318A CN 113483849 A CN113483849 A CN 113483849A
- Authority
- CN
- China
- Prior art keywords
- transformer
- value
- historical
- time
- liquid level
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Fluid Mechanics (AREA)
- Housings And Mounting Of Transformers (AREA)
Abstract
A dynamic monitoring method for the liquid level of transformer features that the historical oil temp, level and alarm data of transformer are analyzed, and the real-time state data of transformer are combined to obtain the median set of level, the current alarm value and the relative gradient of liquid level of transformer, and the alarm trigger condition is calculated and judged.
Description
The technical field is as follows:
the invention relates to the technical field of transformer substation monitoring management, in particular to a transformer liquid level monitoring technology, and specifically relates to a dynamic transformer liquid level monitoring method.
Background art:
in a power system, the liquid level of a transformer in a transformer substation changes along with the change of environmental temperature, the liquid level rises when the environmental temperature rises, and the liquid level falls when the environmental temperature falls, so that the change brings inconvenience to the liquid level alarm of the transformer. In the prior art, a fixed alarm value or gradient alarm mode is usually adopted, but the two modes can not effectively avoid false alarm and false alarm leakage caused by the change of the liquid level of the transformer along with the ambient temperature. Meanwhile, in order to avoid the occurrence of false alarm, the conventional transformer liquid level detection method generally adopts the increase of an alarm limit value, but the method can cover the slow change of the oil temperature of the transformer, so that the corresponding action of the transformer liquid level alarm is lost, and the safe operation of a transformer substation is difficult to effectively ensure.
The invention content is as follows:
the invention aims to provide a dynamic monitoring method for the liquid level of a transformer, which realizes dynamic alarm of the liquid level of the transformer by analyzing the historical oil temperature value, the historical liquid level value and the historical alarm data of the transformer and combining with analysis of real-time state data of the transformer, effectively solves the problems of high false alarm rate and high missing alarm rate caused by setting a fixed alarm value, gradient alarm, increasing the alarm limit value and the like, and has the advantages of low realization cost, high safety degree, reduction of basic investment and improvement of monitoring efficiency.
The invention relates to a dynamic monitoring method for the liquid level of a transformer, which comprises the following steps: the method comprises the following steps: acquiring a historical transformer oil temperature value, a historical transformer liquid level value and historical alarm data in a transformer substation monitoring system, wherein the historical transformer oil temperature value is extracted from the monitoring system, the historical transformer liquid level value is extracted from an image recognition system, the historical alarm data is a transformer alarm record in a transformer substation background monitoring system, and the historical transformer oil temperature value, the historical transformer liquid level value and the historical alarm data at least comprise complete monitoring information of one year; step two: traversing and searching a set of time points k which simultaneously meet the conditions that U (k-1) > l × Un, U (k) > l × Un and S (k) is 0, wherein U (k-1) and U (k) are any voltage values on the primary side of the historical transformer at the time of k-1 and k, S (k) is a historical alarm value of the transformer at the time of k, 0 indicates no alarm, 1 indicates an alarm, Un is a voltage reference value of the voltage level of the transformer, l is a reliability coefficient value of 0.7, and the time interval between the time of k-1 and the time of k is 30 minutes; step three: traversing historical monitoring data, and obtaining a set of a two-dimensional array Tu by a formula Tu (u, k) ═ I (k), wherein I (k) is a transformer liquid level value at the moment k, Tu (u, k) is a liquid level value at the moment k, and the temperature u is obtained by a formula u ═ int (T (k)), wherein T (k) is a transformer oil temperature value at the moment k, and int () is an integer function; step four: traversing the two-dimensional array Tu, calculating to obtain the median of the transformer liquid level value at each temperature u, and storing the result into a Tz set, wherein Tz (u) represents the median value of the liquid level at the temperature u; step five: in the real-time monitoring system, an alarm value A (i) of the current i moment of the transformer is obtained by a formula A (i) ═ Tz (u), wherein the temperature u is obtained by u ═ int (T) (i), T (i) is the temperature value of the transformer oil at the current i moment, int () is an integer function, and if the current temperature u is not in the Tz set of the step four, a median value nearest to u in the Tz set is taken as A (i); step six: calculating a relative gradient value D (i) of the liquid level of the transformer at the current time i by using a formula D (i) ═ fabs (A (i) -A (i-1) -Tz (u.i) + Tz (v.i-1)), wherein the function fabs () is an absolute value function, A (i-1) is an alarm value at the time i-1, Tz (u.i) is a Tz (u) value of the transformer oil temperature u at the time i, Tz (v.i-1) is a Tz (v) value of the transformer oil temperature v at the time i-1, and the time interval between the time i-1 and the time i is 30 minutes; step seven: and (3) taking a transformer level value I (i) at the current moment i, and when I (i) > lambda A (i), or I (i) < (lambda-1) x A (i), or D (i) > (lambda-1) x A (i) are met, wherein lambda is a reliable coefficient value of 1.2, and triggering and alarming by a transformer substation monitoring system.
The working principle of the invention is as follows: acquiring a transformer oil temperature value, a liquid level value and alarm data for at least one year, wherein the larger the scale of the processed historical data is, the higher the precision of the monitoring method is, traversing the historical data to find out a time point k which simultaneously meets three conditions of U (k-1) > l × Un, U (k) > l × Un and S (k) ═ 0, and acquiring a set of the time point k, obtaining a set of two-dimensional array Tu through a set of time points k by a formula Tu (u, k) ═ I (k), traversing the set of two-dimensional array Tu, obtaining a set of median Tz of transformer level values at each temperature u, calculating an alarm value A (i) by a formula A (i) ═ Tz (u), if the temperature u is not hit in the set of Tz, taking a median value in the Tz set which is nearest to the temperature u as A (i), and simultaneously obtaining a relative gradient value D (i) of the liquid level of the transformer at the current time i by a formula.
D (i) ═ fabs (A (i) — A (i-1) -Tz (u.i) + Tz (v.i-1)) is obtained through calculation, after data A (i) and D (i) are obtained through the steps, the system judges that when I (i) > lambda A (i), or I (i) < (lambda-1) xA (i) or D (i) > (lambda-1) xA (i) is met, the substation monitoring system triggers an alarm, and accurate transformer liquid level dynamic monitoring is achieved.
Compared with the prior art, the invention has positive and obvious effect. The invention realizes the dynamic alarm of the liquid level of the transformer by analyzing the historical oil temperature value, the historical liquid level value and the historical alarm data of the transformer and combining the analysis of the real-time state data of the transformer, thereby effectively reducing the problems of false alarm and high missing alarm rate generated by setting a fixed alarm value and a gradient alarm and increasing the alarm limit value and the like.
Description of the drawings:
FIG. 1 is a schematic flow chart of a dynamic monitoring method for the liquid level of a transformer according to the present invention
The specific implementation mode is as follows:
example 1:
as shown in FIG. 1, the dynamic monitoring method for the liquid level of the transformer of the invention comprises the following steps:
the method comprises the following steps: acquiring a historical transformer oil temperature value, a historical transformer liquid level value and historical alarm data in a transformer substation monitoring system, wherein the historical transformer oil temperature value is extracted from the monitoring system, the historical transformer liquid level value is extracted from an image recognition system, the historical alarm data is a transformer alarm record in a transformer substation background monitoring system, and the historical transformer oil temperature value, the historical transformer liquid level value and the historical alarm data at least comprise complete monitoring information of one year;
step two: traversing and searching a set of time points k which simultaneously meet the conditions that U (k-1) > l × Un, U (k) > l × Un and S (k) is 0, wherein U (k-1) and U (k) are any voltage values on the primary side of the historical transformer at the time of k-1 and k, S (k) is a historical alarm value of the transformer at the time of k, 0 indicates no alarm, 1 indicates an alarm, Un is a voltage reference value of the voltage level of the transformer, l is a reliability coefficient value of 0.7, and the time interval between the time of k-1 and the time of k is 30 minutes;
step three: traversing historical monitoring data, and obtaining a set of a two-dimensional array Tu by a formula Tu (u, k) ═ I (k), wherein I (k) is a transformer liquid level value at the moment k, Tu (u, k) is a liquid level value at the moment k, and the temperature u is obtained by a formula u ═ int (T (k)), wherein T (k) is a transformer oil temperature value at the moment k, and int () is an integer function;
step four: traversing the two-dimensional array Tu, calculating to obtain the median of the transformer liquid level value at each temperature u, and storing the result into a Tz set, wherein Tz (u) represents the median value of the liquid level at the temperature u;
step five: in the real-time monitoring system, an alarm value A (i) of the current i moment of the transformer is obtained by a formula A (i) ═ Tz (u), wherein the temperature u is obtained by u ═ int (T) (i), T (i) is the temperature value of the transformer oil at the current i moment, int () is an integer function, and if the current temperature u is not in the Tz set of the step four, a median value nearest to u in the Tz set is taken as A (i);
step six: calculating a relative gradient value D (i) of the liquid level of the transformer at the current time i by using a formula D (i) ═ fabs (A (i) -A (i-1) -Tz (u.i) + Tz (v.i-1)), wherein the function fabs () is an absolute value function, A (i-1) is an alarm value at the time i-1, Tz (u.i) is a Tz (u) value of the transformer oil temperature u at the time i, Tz (v.i-1) is a Tz (v) value of the transformer oil temperature v at the time i-1, and the time interval between the time i-1 and the time i is 30 minutes;
step seven: and (3) taking a transformer level value I (i) at the current moment i, and when I (i) > lambda A (i), or I (i) < (lambda-1) x A (i), or D (i) > (lambda-1) x A (i) are met, wherein lambda is a reliable coefficient value of 1.2, and triggering and alarming by a transformer substation monitoring system.
Claims (1)
1. A dynamic monitoring method for the liquid level of a transformer is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: acquiring a historical transformer oil temperature value, a historical transformer liquid level value and historical alarm data in a transformer substation monitoring system, wherein the historical transformer oil temperature value is extracted from the monitoring system, the historical transformer liquid level value is extracted from an image recognition system, the historical alarm data is a transformer alarm record in a transformer substation background monitoring system, and the historical transformer oil temperature value, the historical transformer liquid level value and the historical alarm data at least comprise complete monitoring information of one year;
step two: traversing and searching a set of time points k which simultaneously meet the conditions that U (k-1) > l × Un, U (k) > l × Un and S (k) is 0, wherein U (k-1) and U (k) are any voltage values on the primary side of the historical transformer at the time of k-1 and k, S (k) is a historical alarm value of the transformer at the time of k, 0 indicates no alarm, 1 indicates an alarm, Un is a voltage reference value of the voltage level of the transformer, l is a reliability coefficient value of 0.7, and the time interval between the time of k-1 and the time of k is 30 minutes;
step three: traversing historical monitoring data, and obtaining a set of a two-dimensional array Tu by a formula Tu (u, k) ═ I (k), wherein I (k) is a transformer liquid level value at the moment k, Tu (u, k) is a liquid level value at the moment k, and the temperature u is obtained by a formula u ═ int (T (k)), wherein T (k) is a transformer oil temperature value at the moment k, and int () is an integer function;
step four: traversing the two-dimensional array Tu, calculating to obtain the median of the transformer liquid level value at each temperature u, and storing the result into a Tz set, wherein Tz (u) represents the median value of the liquid level at the temperature u;
step five: in the real-time monitoring system, an alarm value A (i) of the current i moment of the transformer is obtained by a formula A (i) ═ Tz (u), wherein the temperature u is obtained by u ═ int (T) (i), T (i) is the temperature value of the transformer oil at the current i moment, int () is an integer function, and if the current temperature u is not in the Tz set of the step four, a median value nearest to u in the Tz set is taken as A (i);
step six: calculating a relative gradient value D (i) of the liquid level of the transformer at the current time i by using a formula D (i) ═ fabs (A (i) -A (i-1) -Tz (u.i) + Tz (v.i-1)), wherein the function fabs () is an absolute value function, A (i-1) is an alarm value at the time i-1, Tz (u.i) is a Tz (u) value of the transformer oil temperature u at the time i, Tz (v.i-1) is a Tz (v) value of the transformer oil temperature v at the time i-1, and the time interval between the time i-1 and the time i is 30 minutes;
step seven: and (3) taking a transformer level value I (i) at the current moment i, and when I (i) > lambda A (i), or I (i) < (lambda-1) x A (i), or D (i) > (lambda-1) x A (i) are met, wherein lambda is a reliable coefficient value of 1.2, and triggering and alarming by a transformer substation monitoring system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110747318.6A CN113483849B (en) | 2021-07-01 | 2021-07-01 | Dynamic monitoring method for liquid level of transformer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110747318.6A CN113483849B (en) | 2021-07-01 | 2021-07-01 | Dynamic monitoring method for liquid level of transformer |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113483849A true CN113483849A (en) | 2021-10-08 |
| CN113483849B CN113483849B (en) | 2023-10-17 |
Family
ID=77940118
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110747318.6A Active CN113483849B (en) | 2021-07-01 | 2021-07-01 | Dynamic monitoring method for liquid level of transformer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113483849B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2466322A1 (en) * | 2010-12-17 | 2012-06-20 | ABB Research Ltd. | Method and apparatus for transformer diagnosis |
| CN105893943A (en) * | 2016-03-28 | 2016-08-24 | 国网浙江省电力公司宁波供电公司 | Oil level detection method and system |
| CN107450428A (en) * | 2017-08-08 | 2017-12-08 | 国网重庆市电力公司江津供电分公司 | A kind of main transformer oil level method for real-time monitoring equivalent based on translation |
| CN112001417A (en) * | 2020-07-17 | 2020-11-27 | 国网宁夏电力有限公司检修公司 | Monitoring method, medium and system for transformer oil conservator |
| CN112036436A (en) * | 2020-07-23 | 2020-12-04 | 国网江苏省电力有限公司检修分公司 | Data noise processing method and processing system of phase modulator oil temperature prediction system |
| US20200411233A1 (en) * | 2019-06-27 | 2020-12-31 | Simit Pradhan | Temperature based fluid level estimation in an electrical device |
-
2021
- 2021-07-01 CN CN202110747318.6A patent/CN113483849B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2466322A1 (en) * | 2010-12-17 | 2012-06-20 | ABB Research Ltd. | Method and apparatus for transformer diagnosis |
| CN105893943A (en) * | 2016-03-28 | 2016-08-24 | 国网浙江省电力公司宁波供电公司 | Oil level detection method and system |
| CN107450428A (en) * | 2017-08-08 | 2017-12-08 | 国网重庆市电力公司江津供电分公司 | A kind of main transformer oil level method for real-time monitoring equivalent based on translation |
| US20200411233A1 (en) * | 2019-06-27 | 2020-12-31 | Simit Pradhan | Temperature based fluid level estimation in an electrical device |
| CN112001417A (en) * | 2020-07-17 | 2020-11-27 | 国网宁夏电力有限公司检修公司 | Monitoring method, medium and system for transformer oil conservator |
| CN112036436A (en) * | 2020-07-23 | 2020-12-04 | 国网江苏省电力有限公司检修分公司 | Data noise processing method and processing system of phase modulator oil temperature prediction system |
Non-Patent Citations (1)
| Title |
|---|
| 翟少磊;曹敏;沈鑫;王飞;王恩;: "变电站在线监测多维信息聚合技术", 高电压技术, no. 12 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113483849B (en) | 2023-10-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110895526A (en) | Method for correcting data abnormity in atmosphere monitoring system | |
| CN107451600B (en) | Online photovoltaic hot spot fault detection method based on isolation mechanism | |
| CN112348237A (en) | Dynamic drilling data abnormal trend detection method | |
| CN116308305B (en) | Bridge health monitoring data management system | |
| CN111881594A (en) | Non-stationary signal state monitoring method and system for nuclear power equipment | |
| CN116881673B (en) | Shield tunneling machine operation and maintenance method based on big data analysis | |
| CN103487250B (en) | Based on the coal mine equipment anticipatory maintenance method of two-dimensional projections | |
| CN115220396A (en) | Intelligent monitoring method and system for numerical control machine tool | |
| CN117310517A (en) | Lithium battery voltage state evaluation and early warning method based on big data analysis | |
| CN108333443B (en) | Method for alarming intermittent defects of power equipment | |
| CN113483849A (en) | Dynamic monitoring method for liquid level of transformer | |
| CN117825864A (en) | Power distribution network line short-circuit capacity monitoring and diagnosing method and system | |
| CN101660401B (en) | Real-time alarming method by monitoring shutdown of pumping machine based on acceleration sensor | |
| CN113283014B (en) | New energy automobile operation data analysis processing method, system and storage medium | |
| CN115144172A (en) | GIS breaker fault online monitoring system and method based on sound | |
| CN115859205A (en) | Hydropower station risk early warning method and system based on space-time internet of things | |
| CN115167364A (en) | Early fault detection method based on probability transformation and statistical characteristic analysis | |
| CN114879033A (en) | Motor fault detection method, system and storage medium | |
| CN113297543A (en) | Method and device for calculating service life of cooling water in water cooling system and readable medium | |
| CN108613873B (en) | Beam bridge structure damage positioning method based on joint phase space of double-sensor information | |
| JP2020052676A (en) | State monitor and wind power generator using the same | |
| CN118336877B (en) | Battery charging large model anomaly identification method based on electric power fingerprint | |
| CN116432819A (en) | Key index trend early warning method, system, terminal and storage medium | |
| CN117889121B (en) | Hydraulic cylinder auxiliary locking device | |
| CN115754006B (en) | Acoustic emission event detection method based on time sequence arrangement mode distribution |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |