CN114235053A - Method for improving abnormity detection accuracy of voltage transformation equipment - Google Patents
Method for improving abnormity detection accuracy of voltage transformation equipment Download PDFInfo
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- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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Abstract
The application provides a method for improving the abnormity detection accuracy of a voltage transformation device, which comprises the following steps: the sensing parameter management module periodically reads the sensing parameters of the transformer and stores the sensing parameters into a database; the Temperature detection module acquires an oil Temperature reading value Temperature _ current of the current time point T _ current, and searches a time point T _ last which is less than a Threshold1 than the Temperature _ current last time before the T _ current; the winding state monitoring module calculates the voltage stabilization time T0 of the primary winding and the load stabilization time T1 of the secondary winding, and then selects the minimum time value from T0 and T1 and assigns the minimum time value to T _ min; and the temperature abnormity judging module judges whether the (T _ current-T _ last) is less than T _ min, and if so, reports the transformer temperature abnormity indication. The method has the advantages that the incidence relation between the external factors and the internal factors of the heat generation of the transformer is established, and then the abnormal temperature events caused by the uncertainty of multiple dimensions in the transformer are diagnosed through the consistency of the external factors and the internal factors, so that the accuracy and the timeliness of monitoring and early warning of the abnormal state of the transformer are improved, and the safe operation of the transformation equipment and a power supply system is effectively protected.
Description
Technical Field
The application relates to the field of transformer monitoring, in particular to a method for improving abnormity detection accuracy of a transformer device.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The transformer is an important device in the power system, and the operation reliability of the transformer has a great relation to the safe and reliable operation of the power system. According to statistics of relevant data, the average accident rate of the transformer with the voltage of 110kV and above is about 0.69%, wherein insulation aging is caused due to the over-temperature operation of the winding, the winding is broken down, and the burning accident of the transformer accounts for a large proportion. Therefore, the measurement and monitoring of the temperature of the transformer have extremely important significance for early warning and timely action of transformer accidents.
However, the prior art for monitoring the transformer for abnormality mainly includes the following two methods:
firstly, monitoring whether the temperature of the transformer exceeds a threshold, and if so, judging that the transformer is abnormal. As an improvement, some technical schemes eliminate measurement errors by measuring the temperature for multiple times so as to improve the accuracy of temperature reading and thus improve the monitoring accuracy;
secondly, the temperature value and other physical characteristics (such as oil chromatography) matched with the temperature value are read, then the temperature of the transformer is judged and confirmed to really exceed the threshold through the combination of a plurality of measured parameters, so that the accuracy of temperature sensing is further improved, and then the transformer is judged to be abnormal when the temperature value exceeds the threshold based on the accurately sensed temperature value.
The monitoring strategy for transformer abnormity in the prior art mainly judges whether a transformer is abnormal or not based on whether the temperature exceeds a threshold or not, obviously, if the temperature threshold is set too low, a false alarm is easily caused for transformer abnormity judgment, and therefore troubles are caused for normal power supply and huge overhaul cost is caused; if the threshold is set too high, when it is determined that the temperature of the transformer is found to exceed the threshold, the transformer is likely to be damaged due to the high temperature state for a long time, thereby lengthening the power restoration cycle and easily causing a huge financial loss due to equipment damage.
Therefore, the strategy for judging whether the transformer substation is abnormal based on the temperature threshold in the prior art has the problem of unscientific monitoring, so that a great number of side effects are brought to a power system, and therefore, how to improve the scientificity of transformer monitoring and realize effective monitoring of transformer abnormity early warning is a problem to be solved in the industry.
Disclosure of Invention
The method for improving the abnormity detection accuracy of the transformer equipment is provided for solving the problems, the incidence relation between external factors and internal factors of heat generation of the transformer is established, and then the abnormal temperature events caused by multiple dimensionality uncertainties in the transformer are diagnosed through the consistency of the external factors and the internal factors, so that the accuracy and timeliness of monitoring and early warning of the abnormal state of the transformer are improved, and the safe operation of the transformer equipment and a power supply system is effectively protected.
The application provides a method for improving the accuracy of abnormal detection of a transformer device, which is based on a transformer monitoring device composed of a sensing parameter management module, a temperature detection module, a winding state monitoring module and a temperature abnormity judgment module, and specifically comprises the following steps:
step 1, a sensing parameter management module periodically reads sensing parameters of a transformer and stores the sensing parameters into a database;
step 2, the Temperature detection module obtains the oil Temperature reading value Temperature _ current of the current time point T _ current, and searches the time point T _ last before the T _ current, which is the last time when the ratio of the Temperature _ current is less than the Threshold 1;
step 3, the winding state monitoring module calculates the voltage stabilization time T0 of the primary winding and the load stabilization time T1 of the secondary winding, and then selects the minimum time value from T0 and T1 and assigns the minimum time value to T _ min;
and 4, judging whether the (T _ current-T _ last) is smaller than T _ min by a temperature abnormity judging module, and reporting a transformer temperature abnormity indication if the (T _ current-T _ last) is smaller than T _ min.
Preferably, in step 1, the reading period is completed through presetting, and the sensing parameters at least include a primary winding voltage, a secondary winding load value, and an oil temperature reading value.
Preferably, in step 2, the method for searching for the time point T _ last when the last time ratio Temperature _ current before T _ current is less than the Threshold1 includes:
from T _ current, inquiring an oil Temperature reading value Temperature _ tmp corresponding to the corresponding time point T _ tmp from the database in a time decreasing mode, and then comparing whether the formula (1) is established or not;
(Temperature_current-Temperature_tmp)>Threshold1……(1)
when equation (1) is first satisfied, T _ tmp is assigned to T _ last.
Preferably, in step 3, the method for the winding state monitoring module to calculate the primary winding voltage stabilization time period T0 includes:
acquiring a primary winding voltage sensing value V _ current at the moment of T _ current, then inquiring a winding voltage sensing value V _ tmp corresponding to a corresponding moment point T _ tmp from a database by taking the moment point T _ current as a reference in a time decreasing mode, and then comparing whether a formula (2) is established or not;
abs(V_current-V_tmp)>Threshold2……(2)
when equation (2) is first satisfied, (T _ current-T _ tmp) is assigned to T0.
Preferably, in step 3, the method for the winding state monitoring module to calculate the load stabilization time period T1 of the secondary winding includes:
acquiring a secondary winding load sensing value Payload _ current at the time of T _ current, then inquiring a winding voltage sensing value Payload _ tmp corresponding to the time point T _ tmp from a database by taking the time point T _ current as a reference and according to a time decreasing mode, and then comparing whether the formula (3) is established or not;
abs(Payload_current-Payload_tmp)>Threshold3……(3)
when equation (3) is first satisfied, (T _ current-T _ tmp) is assigned to T1.
Compared with the prior art, the beneficial effect of this application is:
according to the method and the device, the incidence relation between the external factors and the internal factors of the heat generation of the transformer is established, and then the abnormal temperature events caused by the uncertainty of multiple dimensions in the transformer are diagnosed through the consistency of the external factors and the internal factors, so that the accuracy and the timeliness of monitoring and early warning of the abnormal state of the transformer are improved, and the safe operation of the transformation equipment and a power supply system is effectively protected.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a schematic flow chart of a method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of the apparatus components of an embodiment of the present application;
FIG. 3 is a schematic diagram of an embodiment of the present application.
The specific implementation mode is as follows:
the present application will be further described with reference to the following drawings and examples.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only relational terms determined for convenience in describing structural relationships of the parts or elements of the present disclosure, and do not refer to any parts or elements of the present disclosure, and are not to be construed as limiting the present disclosure.
As shown in fig. 1 to 2, the present application provides a method for improving the accuracy of detecting an abnormality of a transformer device, based on the transformer monitoring device provided by the present application, the monitoring device is composed of a transformer monitoring device composed of a sensing parameter management module, a temperature detection module, a winding state monitoring module, and a temperature abnormality determination module, and the functions of each module are as follows:
a sensing parameter management module: the module is responsible for periodically reading the sensing parameters of the transformer and storing the sensing parameters into a database.
A temperature detection module: the module is responsible for obtaining the oil Temperature reading value Temperature _ current of the current time point T _ current and searching the time point T _ last which is less than the Threshold1 than the Temperature _ current last time before the T _ current.
The winding state monitoring module: the module is responsible for calculating the voltage stabilization time length T0 of the primary winding and the load stabilization time length T1 of the secondary winding, and then selecting the minimum time length value from T0 and T1 to assign to T _ min.
A temperature anomaly determination module: the module is responsible for judging whether (T _ current-T _ last) is smaller than T _ min or not, and if yes, reporting an abnormal indication of the temperature of the transformer.
The method for improving the abnormity detection accuracy of the voltage transformation equipment specifically comprises the following steps:
step 1, a sensing parameter management module periodically reads sensing parameters of a transformer and stores the sensing parameters into a database;
step 2, the Temperature detection module obtains the oil Temperature reading value Temperature _ current of the current time point T _ current, and searches the time point T _ last before the T _ current, which is the last time when the ratio of the Temperature _ current is less than the Threshold 1;
step 3, the winding state monitoring module calculates the voltage stabilization time T0 of the primary winding and the load stabilization time T1 of the secondary winding, and then selects the minimum time value from T0 and T1 and assigns the minimum time value to T _ min;
and 4, judging whether the (T _ current-T _ last) is smaller than T _ min by a temperature abnormity judging module, and reporting a transformer temperature abnormity indication if the (T _ current-T _ last) is smaller than T _ min.
Specifically, in step 1, the reading period is completed through presetting, the sensing parameters at least include a primary winding voltage, a secondary winding load value, and an oil temperature reading value, and the secondary winding load value is a secondary winding voltage value.
In step 2, the method for searching for the time point T _ last when the last time ratio Temperature _ current before T _ current is less than the Threshold1 includes:
from T _ current, inquiring an oil Temperature reading value Temperature _ tmp corresponding to the corresponding time point T _ tmp from the database in a time decreasing mode, and then comparing whether the formula (1) is established or not;
(Temperature_current-Temperature_tmp)>Threshold1……(1)
when equation (1) is first satisfied, T _ tmp is assigned to T _ last.
Preferably, in step 3, the method for the winding state monitoring module to calculate the primary winding voltage stabilization time period T0 includes:
acquiring a primary winding voltage sensing value V _ current at the moment of T _ current, then inquiring a winding voltage sensing value V _ tmp corresponding to a corresponding moment point T _ tmp from a database by taking the moment point T _ current as a reference in a time decreasing mode, and then comparing whether a formula (2) is established or not;
abs(V_current-V_tmp)>Threshold2……(2)
when equation (2) is first satisfied, (T _ current-T _ tmp) is assigned to T0.
In step 3, the method for the winding state monitoring module to calculate the load stabilization time T1 of the secondary winding includes:
acquiring a secondary winding load sensing value Payload _ current at the time of T _ current, then inquiring a winding voltage sensing value Payload _ tmp corresponding to the time point T _ tmp from a database by taking the time point T _ current as a reference and according to a time decreasing mode, and then comparing whether the formula (3) is established or not;
abs(Payload_current-Payload_tmp)>Threshold3……(3)
when equation (3) is first satisfied, (T _ current-T _ tmp) is assigned to T1.
The following describes a specific embodiment of a transformer monitoring apparatus with specific examples:
as shown in fig. 3, after the transformer is turned on by the operator, the transformer enters a working state, and at the same time, the transformer monitoring device also enters a monitoring working state:
the sensing parameter management module reads sensing parameters of the transformer once according to a preset period (10 seconds in the embodiment), wherein the sensing parameters comprise primary winding voltage, secondary winding load value and oil temperature reading value, and then the sensing parameters read each time are stored in a database; then the Temperature detection module obtains the oil Temperature reading value Temperature _ current of the current time point T _ current, and searches the time point T _ last before the T _ current, which is less than the Threshold1 than the Temperature _ current last time; then the winding state monitoring module calculates the voltage stabilization time T0 of the primary winding and the load stabilization time T1 of the secondary winding, and then selects the minimum time value from T0 and T1 and assigns the minimum time value to T _ min; in this embodiment, within the previous 990 seconds, the monitoring results (T _ current-T _ last) of the transformer monitoring device are all greater than T _ min, so that the temperature of the transformer is considered to be normal, and the sensing parameter management module reads the sensing parameters of the transformer and stores the sensing parameters in the database after 1000 seconds (i.e., 100 th reading period); then the Temperature detection module obtains the oil Temperature reading value Temperature _ current of the current time point T _ current, and searches for the time point T _ last (as shown in fig. 3, in this embodiment, T _ current is 1000 seconds, and T _ last is 380 seconds) at the last time before T _ current when the Temperature _ current is smaller than the Threshold value Threshold 1; then the winding state monitoring module calculates a primary winding voltage stabilization duration T0 (as shown in fig. 3, in this embodiment, T _ current is 1000 seconds, and T _ tmp is 0 second, so T0 is equal to 1000 seconds), a secondary winding load stabilization duration T1 (as shown in fig. 3, in this embodiment, T _ current is 1000 seconds, and T _ tmp is 80 seconds, so T1 is equal to 920 seconds), and then selects a minimum duration value from T0 and T1 and assigns the minimum duration value to T _ min (at this time, T _ min is 920 seconds); then, the temperature anomaly determination module determines that (T _ current-T _ last) — (1000-. In the embodiment, whether the transformer is abnormal or not is diagnosed by monitoring and calculating the latest stable time of the external factor generated by the temperature of the transformer and the time corresponding to the starting and stopping time point of the oil temperature reading step of the transformer, and then judging the consistency of the two times, wherein in the embodiment, the time corresponding to the starting and stopping time point of the oil temperature reading step is shorter than the latest stable time of the external factor generated by the temperature of the transformer, which indicates that the fault occurs inside the transformer system (possibly the temperature sensing read value is abnormal, the cooling module is abnormal, the winding is possibly failed, and the like, and under the condition that the external factor is not changed, the temperature of the transformer generates the temperature step), the read oil temperature is broken through the balance, the step is further judged to occur, the temperature of the transformer is abnormal, and the abnormal indication is reported, in the embodiment, the temperature of the transformer at the abnormal time point is judged not to exceed the threshold mentioned in the prior art, however, by the method, even if the temperature does not exceed the threshold after the internal and external factors are judged to be inconsistent, the method can also early warn and diagnose that the inside of the transformer is abnormal, and because the temperature is not high when the abnormality occurs, the background control center can effectively protect the transformer from being damaged by stopping the transformer, so the method can improve the accuracy and timeliness of monitoring and early warning of the abnormal state of the transformer and effectively protect the safe operation of the transformer equipment and a power supply system.
According to the embodiment, the correlation between the external factors and the internal factors of the heat generation of the transformer is established, and then the abnormal temperature events caused by the uncertainty of multiple dimensions in the transformer are diagnosed according to the consistency of the external factors and the internal factors, so that the accuracy and the timeliness of monitoring and early warning of the abnormal state of the transformer are improved, and the safe operation of the transformer equipment and a power supply system is effectively protected.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Although the embodiments of the present application have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present application, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive effort by those skilled in the art.
Claims (5)
1. A method for improving the abnormity detection accuracy of a voltage transformation device is characterized by comprising the following steps: the transformer monitoring device based on the sensor parameter management module, the temperature detection module, the winding state monitoring module and the temperature abnormity judgment module comprises the following steps:
step 1, a sensing parameter management module periodically reads sensing parameters of a transformer and stores the sensing parameters into a database;
step 2, the Temperature detection module obtains the oil Temperature reading value Temperature _ current of the current time point T _ current, and searches the time point T _ last before the T _ current, which is the last time when the ratio of the Temperature _ current is less than the Threshold 1;
step 3, the winding state monitoring module calculates the voltage stabilization time T0 of the primary winding and the load stabilization time T1 of the secondary winding, and then selects the minimum time value from T0 and T1 and assigns the minimum time value to T _ min;
and 4, judging whether the (T _ current-T _ last) is smaller than T _ min by a temperature abnormity judging module, and reporting a transformer temperature abnormity indication if the (T _ current-T _ last) is smaller than T _ min.
2. The method for improving the accuracy of detecting the abnormality of the voltage transformation equipment according to claim 1, wherein:
in the step 1, the reading period is completed through presetting, and the sensing parameters at least comprise a primary winding voltage, a secondary winding load value and an oil temperature reading value.
3. The method for improving the accuracy of detecting the abnormality of the voltage transformation equipment according to claim 2, wherein:
in step 2, the method for searching for the time point T _ last when the last time ratio Temperature _ current before T _ current is less than the Threshold1 includes:
from T _ current, inquiring an oil Temperature reading value Temperature _ tmp corresponding to the corresponding time point T _ tmp from the database in a time decreasing mode, and then comparing whether the formula (1) is established or not;
(Temperature_current-Temperature_tmp)>Threshold1……(1)
when equation (1) is first satisfied, T _ tmp is assigned to T _ last.
4. The method for improving the accuracy of detecting the abnormality of the voltage transformation equipment according to claim 2, wherein:
in step 3, the method for the winding state monitoring module to calculate the primary winding voltage stabilization time period T0 includes:
acquiring a primary winding voltage sensing value V _ current at the moment of T _ current, then inquiring a winding voltage sensing value V _ tmp corresponding to a corresponding moment point T _ tmp from a database by taking the moment point T _ current as a reference in a time decreasing mode, and then comparing whether a formula (2) is established or not;
abs(V_current-V_tmp)>Threshold2……(2)
when equation (2) is first satisfied, (T _ current-T _ tmp) is assigned to T0.
5. The method for improving the accuracy of detecting the abnormality of the voltage transformation equipment according to claim 2, wherein:
in step 3, the method for the winding state monitoring module to calculate the load stabilization time T1 of the secondary winding includes:
acquiring a secondary winding load sensing value Payload _ current at the time of T _ current, then inquiring a winding voltage sensing value Payload _ tmp corresponding to the time point T _ tmp from a database by taking the time point T _ current as a reference and according to a time decreasing mode, and then comparing whether the formula (3) is established or not;
abs(Payload_current-Payload_tmp)>Threshold3……(3)
when equation (3) is first satisfied, (T _ current-T _ tmp) is assigned to T1.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060201264A1 (en) * | 2004-04-07 | 2006-09-14 | Hitachi Industrial Equipment Co., Ltd. | Transformer monitoring system |
| CN103592545A (en) * | 2013-11-22 | 2014-02-19 | 国家电网公司 | Transformer temperature rise abnormity monitoring and diagnosis method based on probability statistics |
| CN105975709A (en) * | 2016-05-16 | 2016-09-28 | 中国石油大学(华东) | Transformer hotspot temperature predicting method for multi-working-condition-parameter recognition and optimization |
| CN107272486A (en) * | 2017-06-17 | 2017-10-20 | 丹凤县鑫伟电子有限公司 | A kind of transformer control system and monitoring method |
| CN110007182A (en) * | 2019-03-22 | 2019-07-12 | 中国电力科学研究院有限公司 | A kind of the health status method for early warning and device of distribution transformer |
| CN111856169A (en) * | 2019-04-22 | 2020-10-30 | 宁波奥克斯高科技有限公司 | Transformer fault detection method and system |
| CN111929618A (en) * | 2020-08-25 | 2020-11-13 | 广东电网有限责任公司 | Transformer monitoring method and monitoring system |
-
2021
- 2021-12-20 CN CN202111563468.8A patent/CN114235053B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060201264A1 (en) * | 2004-04-07 | 2006-09-14 | Hitachi Industrial Equipment Co., Ltd. | Transformer monitoring system |
| CN103592545A (en) * | 2013-11-22 | 2014-02-19 | 国家电网公司 | Transformer temperature rise abnormity monitoring and diagnosis method based on probability statistics |
| CN105975709A (en) * | 2016-05-16 | 2016-09-28 | 中国石油大学(华东) | Transformer hotspot temperature predicting method for multi-working-condition-parameter recognition and optimization |
| CN107272486A (en) * | 2017-06-17 | 2017-10-20 | 丹凤县鑫伟电子有限公司 | A kind of transformer control system and monitoring method |
| CN110007182A (en) * | 2019-03-22 | 2019-07-12 | 中国电力科学研究院有限公司 | A kind of the health status method for early warning and device of distribution transformer |
| CN111856169A (en) * | 2019-04-22 | 2020-10-30 | 宁波奥克斯高科技有限公司 | Transformer fault detection method and system |
| CN111929618A (en) * | 2020-08-25 | 2020-11-13 | 广东电网有限责任公司 | Transformer monitoring method and monitoring system |
Non-Patent Citations (1)
| Title |
|---|
| 郭志红等: "油浸电力变压器过载能力核算模型参数敏感性研究", 《电气技术》, no. 09, 15 September 2016 (2016-09-15), pages 77 - 82 * |
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