CN117554735A - Transformer oil temperature abnormality early warning method and device, storage medium and computer equipment - Google Patents
Transformer oil temperature abnormality early warning method and device, storage medium and computer equipment Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims description 30
- 238000013524 data verification Methods 0.000 claims description 17
- 230000007613 environmental effect Effects 0.000 claims description 9
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- 238000004590 computer program Methods 0.000 claims description 8
- 238000012544 monitoring process Methods 0.000 abstract description 12
- 230000008054 signal transmission Effects 0.000 description 9
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/003—Environmental or reliability tests
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K1/00—Details of thermometers not specially adapted for particular types of thermometer
- G01K1/02—Means for indicating or recording specially adapted for thermometers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K15/00—Testing or calibrating of thermometers
- G01K15/007—Testing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/62—Testing of transformers
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/185—Electrical failure alarms
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
The invention discloses a transformer oil temperature abnormality early warning method, a device, a storage medium and computer equipment. Relates to the field of power equipment monitoring. The method comprises the following steps: acquiring target oil temperature data of a target transformer, determining whether the target oil temperature data is wrong, and if so, generating a data error early warning; if the oil temperature data is correct, executing the following steps: determining whether the target oil temperature data reaches a basic overrun threshold value, and if so, generating a threshold overrun early warning; obtaining oil temperature data of a comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a cross ratio overrun threshold according to the comparison oil temperature data, and if so, generating a cross ratio overrun early warning; and calculating predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating predicted overrun early warning. The method can improve the accuracy of early warning of abnormal oil temperature.
Description
Technical Field
The invention relates to the technical field of power equipment monitoring, in particular to a transformer oil temperature abnormality early warning method, a device, a storage medium and computer equipment.
Background
Transformers are an important component in power systems, and are related to safe and stable operation of the power systems. The oil temperature of the transformer is an important parameter reflecting the running state of the transformer, and meanwhile, the oil temperature can also indirectly reflect the working effect of a cooler, a meter for monitoring the oil temperature, the working state of a signal transmission loop and the like. The too high oil temperature may be the abnormal operation of the transformer or the fault of the transformer itself, or the situations that the input strategy of the cooler is improper, the cooling efficiency is reduced, or the fault of a gauge for monitoring the oil temperature or a signal transmission loop occurs. Therefore, the method has important significance in accurately monitoring the oil temperature of the transformer, timely identifying the oil temperature which possibly has abnormality, and timely adopting operation, maintenance and overhaul strategies subsequently and preventing the power grid power failure accident caused by serious faults of the transformer.
The traditional early warning of the transformer oil temperature is usually realized according to whether the transformer oil temperature exceeds a standard threshold value, but practical experience shows that when the transformer oil temperature exceeds the standard threshold value, the transformer has abnormal operation or self-fault and other conditions, and the early warning function cannot be realized under the conditions. And when the transformer load is low, even if the transformer has an abnormal condition, the oil temperature may not exceed the standard threshold value, and in such a case, the missing judgment may occur. In addition, if the oil temperature of the transformer is not abnormal, but a meter for monitoring the oil temperature or a signal transmission loop fails, false oil temperature data can be acquired under the condition, and the fault can not be found in time. Therefore, a method for early warning of abnormal transformer oil temperature is needed so as to timely and accurately identify abnormal conditions of transformer oil temperature and facilitate safe and stable operation of a transformer.
Disclosure of Invention
In view of the above, the application provides a method, a device, a storage medium and computer equipment for early warning of abnormal transformer oil temperature, which mainly aims to solve the technical problems of untimely and inaccurate early warning of the traditional transformer oil temperature early warning method.
According to a first aspect of the invention, there is provided a method for early warning of abnormal oil temperature of transformer, the method comprising:
acquiring target oil temperature data of a target transformer, determining whether the target oil temperature data is wrong, and if so, generating a data error early warning; if not, executing the following steps:
determining whether the target oil temperature data reaches a basic overrun threshold value, and if so, generating threshold overrun early warning;
obtaining oil temperature data of a comparison transformer to obtain comparison oil temperature data, determining whether target oil temperature data reach a cross ratio overrun threshold according to the comparison oil temperature data, and if so, generating a cross ratio overrun early warning;
and calculating to obtain predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating a predicted overrun early warning.
Optionally, determining whether the target oil temperature data is erroneous includes:
Determining whether the oil temperature data meets a data verification condition, wherein the data verification condition is any one of null, zero and negative number of the oil temperature data;
if the data verification condition is met, determining that the oil temperature data is wrong;
if the data verification condition is not met, the oil temperature data is determined to be correct.
Optionally, determining whether the target oil temperature data reaches the basic overrun threshold, if so, generating a threshold overrun early warning, including:
obtaining a cooling mode of a target transformer;
if the target oil temperature data is greater than or equal to a first basic overrun threshold corresponding to the cooling mode, generating a first-level threshold overrun early warning;
if the target oil temperature data is larger than a second basic overrun threshold corresponding to the cooling mode and smaller than the first basic overrun threshold, or the target oil temperature data is equal to the second basic overrun threshold, generating a second-level threshold overrun early warning;
wherein the first base overrun threshold is greater than the second base overrun threshold.
Optionally, before obtaining the oil temperature data of the reference transformer to obtain the reference oil temperature data, determining whether the target oil temperature data reaches the threshold value of the cross ratio overrun according to the reference oil temperature data, the method further includes:
the method comprises the steps of obtaining the model, the capacity and the cooling mode of each transformer of a transformer station where a target transformer is located, and determining whether similar transformers with the same model, capacity and cooling mode as those of the target transformer exist in the transformer station;
If at least one similar transformer exists, load current and rated current of the target transformer and each similar transformer are obtained, and average load rates of the target transformer and each similar transformer in the current time period are calculated according to the load current and the rated current;
obtaining a target load rate according to the average load rate of the target transformer;
calculating the average value of the average load rates of the target transformer and each similar transformer to obtain a comparison load rate;
and calculating the difference between the target load rate and the comparison load rate to obtain a load rate difference value, and if the absolute value of the load rate difference value is smaller than a load rate difference threshold value, setting the similar transformers as comparison transformers for mutual ratio analysis.
Optionally, obtaining oil temperature data of the reference transformer to obtain reference oil temperature data, determining whether the target oil temperature data reaches a threshold value of the cross ratio overrun according to the reference oil temperature data, and if so, generating a pre-warning of the cross ratio overrun, including:
acquiring reference oil temperature data of each reference transformer, and calculating the average value of the target oil temperature data and the reference oil temperature data to obtain average oil temperature data;
calculating the difference between the target oil temperature data and the average oil temperature data to obtain first difference data, and obtaining oil temperature mutual difference data according to the ratio between the first difference data and the average oil temperature data;
Determining a numerical interval corresponding to the target oil temperature data;
and if the oil temperature mutual difference data is larger than or equal to the mutual ratio overrun threshold corresponding to the numerical interval, generating a mutual ratio overrun early warning.
Optionally, calculating by using a preset oil temperature prediction model to obtain predicted oil temperature data of the target transformer, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating a predicted overrun early warning, including:
the method comprises the steps of obtaining load current, rated current and environmental temperature of a target transformer, inputting the load current, the rated current and the environmental temperature into an oil temperature prediction model, and calculating to obtain predicted oil temperature data of the target transformer by using the oil temperature prediction model;
calculating a difference value between the target oil temperature data and the predicted oil temperature data to obtain second difference value data, and obtaining oil temperature error data according to a ratio between the second difference value data and the predicted oil temperature data;
determining a numerical interval corresponding to the target oil temperature data;
and if the oil temperature error data is greater than or equal to the predicted overrun threshold corresponding to the numerical interval, generating predicted overrun early warning.
Optionally, the method further comprises:
each transformer of the transformer substation is set as a target transformer one by one to perform oil temperature early warning detection, and an oil temperature early warning detection result is obtained, wherein the oil temperature early warning detection result comprises at least one of data error early warning, threshold overrun early warning, mutual ratio overrun early warning and prediction overrun early warning;
Counting the oil temperature early warning detection result of the transformer based on at least one statistical dimension of the type, cooling mode, capacity and environmental temperature of the transformer to obtain an early warning statistical result, wherein the early warning statistical result comprises an early warning type and an early warning frequency corresponding to each statistical dimension;
and generating a visual chart according to the early warning statistical result and displaying the visual chart.
According to a second aspect of the present invention, there is provided a transformer oil temperature abnormality warning apparatus, comprising:
the data error early warning module is used for acquiring target oil temperature data of the target transformer, determining whether the target oil temperature data is in error or not, and if so, generating data error early warning;
the threshold overrun early warning module is used for determining whether the target oil temperature data reach a basic overrun threshold, and if so, generating threshold overrun early warning;
the mutual ratio overrun early warning module is used for acquiring the oil temperature data of the comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a mutual ratio overrun threshold according to the comparison oil temperature data, and if so, generating a mutual ratio overrun early warning;
the prediction overrun early warning module is used for calculating and obtaining prediction oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a prediction overrun threshold value according to the prediction oil temperature data, and if so, generating the prediction overrun early warning.
According to a third aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described transformer oil temperature abnormality warning method.
According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above-mentioned method for pre-warning of abnormal transformer oil temperature when executing the program.
According to the transformer oil temperature abnormality early warning method, the transformer oil temperature abnormality early warning device, the storage medium and the computer equipment, target oil temperature data of a target transformer are obtained, whether errors occur in the target oil temperature data or not is determined, and if yes, data error early warning is generated; if the oil temperature data is correct, executing the following steps: determining whether the target oil temperature data reaches a basic overrun threshold value, and if so, generating a threshold overrun early warning; obtaining oil temperature data of a comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a cross ratio overrun threshold according to the comparison oil temperature data, and if so, generating a cross ratio overrun early warning; and calculating predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating predicted overrun early warning. According to the method, whether the oil temperature meter and the signal transmission loop of the transformer are in problem or not can be identified by determining whether the oil temperature data are wrong or not, if yes, data error early warning is generated, and transformer oil temperature monitoring vacuum is avoided; the transformer with excessively high oil temperature can be found in advance to a greater extent through threshold overrun early warning so as to strive for the time of sufficient inspection and maintenance; the transformer with the problems of improper cooler investment strategy, low cooler efficiency, self fault and the like can be identified by the mutual ratio overrun early warning and the predictive overrun early warning. The transformer oil temperature is detected in a plurality of modes simultaneously, so that the transformer with abnormal oil temperature can be timely and accurately identified, early warning can be timely sent out, related personnel are prompted to take measures, and the safe and stable operation of the transformer is ensured.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 shows a schematic flow chart of a method for early warning of abnormal transformer oil temperature according to an embodiment of the present invention;
fig. 2 shows a schematic structural diagram of a transformer oil temperature abnormality early warning device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a storage medium and a computer device according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
In the various embodiments of the present application, the "first", "second" and various numerical numbers are merely for convenience of description and are not intended to limit the scope of the embodiments of the present application. "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship.
In one embodiment, as shown in fig. 1, a method for early warning of abnormal transformer oil temperature is provided, which includes the following steps:
101. acquiring target oil temperature data of a target transformer, determining whether the target oil temperature data is wrong, and if so, generating a data error early warning; if not, executing the following steps:
102. and determining whether the target oil temperature data reaches a basic overrun threshold value, and if so, generating threshold overrun early warning.
103. And acquiring oil temperature data of the comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a cross ratio overrun threshold according to the comparison oil temperature data, and if so, generating a cross ratio overrun early warning.
104. And calculating to obtain predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating a predicted overrun early warning.
Conventional transformer oil temperature early warning is usually carried out only according to whether the transformer oil temperature exceeds a standard threshold value, but the effect of carrying out oil temperature abnormality judgment by only relying on the standard threshold value is limited, and the judgment is possibly missed. For example, in the power industry standard DL/T572-2021, a standard threshold value of the oil temperature of the forced oil circulation air-cooled type transformer is 85 ℃, and a standard threshold value of the oil temperature of the natural circulation self-cooling and air-cooled type transformer is 95 ℃, however, according to practical application, it is found that when the transformer oil temperature is close to or far below the standard threshold value, the transformer is likely to have problems such as abnormal cooling and heat dissipation or failure of the transformer itself, and when the transformer oil temperature is detected to reach the standard threshold value, the early warning is performed later. And when the load of the transformer is lighter, even if the transformer has an abnormal condition, the oil temperature of the transformer is not very high, and the oil temperature does not exceed the standard threshold value, and the early warning is carried out according to the standard threshold value, so that the situation of missed judgment exists. In addition, if the oil temperature of the transformer itself is not problematic, but the oil temperature gauge or the signal transmission circuit is problematic, erroneous oil temperature data can be monitored, and at this time, the early warning should be directed to the oil temperature monitoring aspect, which may be problematic.
Aiming at the possible problems, the embodiment firstly determines whether the target oil temperature data has the problem of data errors when acquiring the oil temperature data of the target transformer to obtain the target oil temperature data, and if the detected target oil temperature data has errors, generates data error early warning to prompt related personnel to check an oil temperature gauge and a signal transmission loop so as to avoid influencing oil temperature monitoring due to the data errors. If the target oil temperature data is confirmed to be free from errors, threshold overrun detection, mutual ratio overrun detection and prediction overrun detection are respectively carried out on the target transformer, and corresponding early warning information is generated according to detection results corresponding to each detection.
In the threshold overrun detection in this embodiment, the basic overrun threshold is lower than the standard threshold specified by the power industry, the transformer whose oil temperature may exceed the standard threshold can be detected as early as possible by comparing the target oil temperature data with the basic overrun threshold, and if the target oil temperature data is greater than or equal to the basic overrun threshold, the threshold overrun early warning is generated, so that relevant personnel are prompted to check the possible problems of the transformer and monitor the transformer heavy points. In the detection of the cross ratio overrun, a comparison transformer for cross ratio analysis is screened out from a transformer station where a target transformer is located, oil temperature data of the comparison transformer is obtained to obtain comparison oil temperature data, the target oil temperature data of the target transformer is compared with the comparison oil temperature data to determine whether the target oil temperature data reaches a cross ratio overrun threshold, and if the target oil temperature data reaches the cross ratio overrun threshold, a cross ratio overrun early warning is generated. In the prediction overrun detection, comparing the target oil temperature data of the target transformer with the predicted oil temperature data obtained through calculation of an oil temperature prediction model, determining whether the target oil temperature data reaches a prediction overrun threshold, and if the target oil temperature data reaches the prediction overrun threshold, generating a prediction overrun early warning. If the oil temperature data of the target transformer is correct and the basic overrun threshold, the mutual ratio overrun threshold and the predicted overrun threshold are not reached, the condition that the oil temperature of the transformer is abnormal is indicated, and the oil temperature normal prompt message is generated.
According to the transformer oil temperature abnormality early warning method provided by the embodiment, whether the transformer oil temperature meter and the signal transmission loop have problems can be identified by determining whether oil temperature data are wrong or not, if yes, data error early warning is generated, and transformer oil temperature monitoring vacuum is avoided; the transformer with excessively high oil temperature can be found in advance to a greater extent through threshold overrun early warning so as to strive for the time of sufficient inspection and maintenance; the transformer with the problems of improper cooler investment strategy, low cooler efficiency, self fault and the like can be identified by the mutual ratio overrun early warning and the predictive overrun early warning. The transformer with abnormal oil temperature can be timely and accurately identified by carrying out early warning detection on the oil temperature of the transformer in various modes, so that early warning can be timely sent out, related personnel can be prompted to take measures, and safe and stable operation of the transformer is ensured.
In an alternative embodiment, the method for determining whether the target oil temperature data is erroneous in step 103 may be implemented specifically by the following steps: determining whether the oil temperature data meets a data verification condition, wherein the data verification condition is any one of null, zero and negative number of the oil temperature data; if the data verification condition is met, determining that the oil temperature data is wrong, namely if the monitored target oil temperature data is null or 0 or negative, proving that the data acquisition or signal transmission link corresponding to the target transformer has problems, and the acquired target oil temperature data is wrong. The data verification condition may further include that the oil temperature data does not exceed a maximum oil temperature threshold, for example, the oil temperature does not exceed 200 ℃ when the transformer is operating normally, and if the obtained target oil temperature data exceeds 200 ℃, the oil temperature data may be determined to be wrong, where 200 ℃ is only used for illustration of the present embodiment, and is not limited to the present embodiment, and the maximum oil temperature threshold may be specifically set according to the actual situation. If the data verification condition is not met, namely the target oil temperature data is not null, is not 0 and is not negative, or the target oil temperature data is within an oil temperature interval corresponding to the operation of the transformer, determining that the oil temperature data is error-free.
In an optional embodiment, in step 102, it is determined whether the target oil temperature data reaches the basic overrun threshold, and if so, the method for generating the threshold overrun early warning may be implemented specifically by the following steps: obtaining a cooling mode of a target transformer; if the target oil temperature data is greater than or equal to a first basic overrun threshold corresponding to the cooling mode, generating a first-level threshold overrun early warning; if the target oil temperature data is larger than a second basic overrun threshold corresponding to the cooling mode and smaller than the first basic overrun threshold, or the target oil temperature data is equal to the second basic overrun threshold, generating a second-level threshold overrun early warning; wherein the first base overrun threshold is greater than the second base overrun threshold.
In the above embodiment, the cooling modes of the transformer include forced oil circulation air cooling, natural circulation self-cooling, air cooling and the like, and the cooling effects generated by different cooling are different, so different basic overrun thresholds are correspondingly set for different cooling modes. And setting at least two grades for the basic overrun threshold of each cooling mode, namely a first basic overrun threshold and a second basic overrun threshold, wherein the first basic overrun threshold is larger than the second basic overrun threshold, and the first basic overrun threshold and the second basic overrun threshold are lower than standard thresholds regulated by the electric power industry so as to discover the abnormal rising of the oil temperature in time. For example, for a forced oil circulation air-cooled type, the standard threshold is 85 ℃, then the first base overrun threshold may be set at 80 ℃, and the second base overrun threshold may be set at 75 ℃. For natural circulation self-cooling, air-cooling types, the standard threshold is 95 ℃, the first base overrun threshold may be set at 85 ℃, and the second base overrun threshold may be set at 80 ℃. If the cooling mode of the target transformer is forced oil circulation air cooling type, if the target oil temperature is equal to 75 ℃, or is more than 75 ℃ and less than 80 ℃, generating a secondary threshold overrun early warning, and if the target oil temperature is more than or equal to 80 ℃, generating a primary threshold overrun early warning.
In the above embodiment, a time stamp when the target oil temperature data reaches the second basic overrun threshold and/or the first basic overrun threshold may be further obtained, a time interval between the target oil temperature data reaching the second basic overrun threshold and the first basic overrun threshold may be calculated, and a rate of oil temperature increase may be determined according to the time interval, so that a user may measure the severity of the abnormal oil temperature of the target transformer, and check and maintain the target transformer as soon as possible. And counting the time when the target oil temperature data reaches the basic overrun threshold, analyzing the relationship between the law of abnormal increase of the oil temperature and the time, and if a high-frequency time period for abnormal increase of the oil temperature exists, selecting a corresponding cooling strategy and a transformer maintenance strategy for the time period so as to protect the service life of the transformer.
In an alternative embodiment, in step 103, before obtaining the oil temperature data of the reference transformer to obtain the reference oil temperature data, determining whether the target oil temperature data reaches the threshold value of overrun of the mutual ratio according to the reference oil temperature data, the method for screening the reference transformer in the transformer substation where the target transformer is located may be implemented specifically by the following steps: the method comprises the steps of obtaining the model, the capacity and the cooling mode of each transformer of a transformer station where a target transformer is located, and determining whether similar transformers with the same model, capacity and cooling mode as those of the target transformer exist in the transformer station; if at least one similar transformer exists, load current and rated current of the target transformer and each similar transformer are obtained, and average load rates of the target transformer and each similar transformer in the current time period are calculated according to the load current and the rated current; obtaining a target load rate according to the average load rate of the target transformer; calculating the average value of the average load rates of the target transformer and each similar transformer to obtain a comparison load rate; and calculating the difference between the target load rate and the comparison load rate to obtain a load rate difference value, and if the absolute value of the load rate difference value is smaller than a load rate difference threshold value, setting the similar transformers as comparison transformers for mutual ratio analysis.
In the above embodiment, before the target transformer is subjected to the mutual comparison analysis, it is first determined whether the target transformer meets the mutual comparison analysis condition, that is, whether at least one control transformer that can be used for the mutual comparison analysis exists in the substation where the target transformer is located. The comparison transformer is the transformer which has the same model, capacity and cooling mode as the target transformer and has similar load rate. The types of transformers are various, and the types of transformers generally include information such as numbers and codes representing a transformer coupling mode, a phase number, a cooling mode, a winding number, a wire material, a voltage regulation mode, a design code (or performance level), a special purpose or a special structure, and a rated capacity, a rated voltage level, a protection level and the like of the transformer. The judgment as to whether the load rates are similar is achieved by the following means: the similar transformers with the same model, capacity and cooling mode as the target transformers are screened out from the transformer substation, the load current data and rated current data of the target transformers and each similar transformer in a preset time period at the current moment are obtained (for example, the current moment is 9 points, the preset time period is 3 hours, the load current data and rated current data of the target transformers and each similar transformer in 6 points to 9 points are obtained), and the load current data and the rated current data are obtained according to the load current data and the rated current data The rated current data respectively calculate the average load rate of the target transformer and the average load rate of each similar transformer in the current time period, and obtain the target load rate K according to the average load rate of the target transformer x Calculating the arithmetic average value of the average load rate of the target transformer and the average load rate of each similar transformer to obtain a comparison load rate K a . Calculating a target load factor K x And contrast to the load factor K a The difference is used to obtain the load factor difference H 0 I.e. H 0 ＝K x -K a . If the absolute value of the load factor difference is smaller than the load factor difference threshold, for example, the load factor difference threshold may be set to 5%, if H 0 If the absolute value of the transformer is smaller than 5%, judging that the load rates of the similar transformers and the target transformers are similar, wherein the similar transformers can be used as comparison transformers for mutual comparison analysis; if H 0 If the absolute value of the voltage is larger than 5%, the load rates of the similar transformers and the target transformers are not similar, namely the operation working conditions of the similar transformers and the target transformers are large in difference, and the similar transformers are not suitable to be used as comparison transformers.
In an optional embodiment, in step 103, the oil temperature data of the reference transformer is obtained to obtain reference oil temperature data, and whether the target oil temperature data reaches the threshold value of the cross ratio overrun is determined according to the reference oil temperature data, and if yes, the method for generating the cross ratio overrun early warning is specifically implemented by the following steps: acquiring reference oil temperature data of each reference transformer, and calculating the average value of the target oil temperature data and the reference oil temperature data to obtain average oil temperature data; calculating the difference between the target oil temperature data and the average oil temperature data to obtain first difference data, and obtaining oil temperature mutual difference data according to the ratio between the first difference data and the average oil temperature data; determining a numerical interval corresponding to the target oil temperature data; and if the oil temperature mutual difference data is larger than or equal to the mutual ratio overrun threshold corresponding to the numerical interval, generating a mutual ratio overrun early warning.
In the above embodiment, the target oil temperature data T of the target transformer is acquired 1 Calculating average value of target oil temperature data and reference oil temperature data to obtain average oil temperature data T a Calculating target oil temperature data T 1 And average oil temperature data T a The difference between them results in first difference data (T 1 -T a ) Calculating first difference data and average oil temperature data T a To obtain the oil temperature mutual difference data H 1 I.e. H 1 ＝(T 1 -T a )/T a . Judging the mutual difference data H of oil temperature 1 Whether or not the mutual ratio overrun threshold R is reached 1 If H 1 Greater than or equal to R 1 And judging that the target transformer has the mutual ratio overrun, and generating a mutual ratio overrun early warning. Wherein the mutual ratio exceeds a threshold R 1 The method is comprehensively determined according to the type of the transformer, the cooling mode, the oil temperature value and the early warning precision, is not smaller than 5% at the same time, can be set in sections according to the numerical value interval corresponding to the target oil temperature data of the transformer to be target, and can be properly adjusted according to practical experience. For example, when the numerical range corresponding to the target oil temperature data is between 30 ℃ and 50 ℃, the mutual ratio exceeds the threshold R 1 Can take 10 percent of value, when the value interval corresponding to the target oil temperature data is between 50 ℃ and 75 ℃, the mutual ratio exceeds the threshold R 1 The value can be 7.5%, when the value interval corresponding to the target oil temperature data is above 75 ℃, the mutual ratio exceeds the threshold R 1 The value is 5%. For example, if the target oil temperature data of the target transformer is 68 ℃ and the average temperature data of the reference transformer is 60 ℃, the oil temperature mutual difference data H 1 = (68 ℃ -60 ℃) 60 ℃. Apprxeq.13.3%, 13.3% is greater than 7.5%, and then the mutual ratio overrun early warning is generated.
In an optional embodiment, in step 104, the predicted oil temperature data of the target transformer is obtained by calculating using a preset oil temperature prediction model, and whether the target oil temperature data reaches the predicted overrun threshold value is determined according to the predicted oil temperature data, and if yes, the method for generating the predicted overrun early warning is specifically implemented by the following steps: the method comprises the steps of obtaining load current, rated current and environmental temperature of a target transformer, inputting the load current, the rated current and the environmental temperature into an oil temperature prediction model, and calculating to obtain predicted oil temperature data of the target transformer by using the oil temperature prediction model; calculating a difference value between the target oil temperature data and the predicted oil temperature data to obtain second difference value data, and obtaining oil temperature error data according to a ratio between the second difference value data and the predicted oil temperature data; determining a numerical interval corresponding to the target oil temperature data; and if the oil temperature error data is greater than or equal to the predicted overrun threshold corresponding to the numerical interval, generating predicted overrun early warning.
In the above embodiment, the oil temperature prediction model is as follows:
k is the load rate of the target transformer; r is the ratio of load loss to no-load loss under rated current; x is the exponent power (oil index) of the total loss to the temperature rise of the top layer oil (in the oil tank) of the target transformer; Δθ or Steady-state temperature rise of top-level oil (in the oil tank) under rated loss (no-load loss + load loss); k (k) 11 Is a thermal model constant; τ o An average oil time constant; t (T) p Predicted oil temperature data for the target transformer; θ a Is the ambient temperature at which the target transformer is located.
In the above embodiment, based on the preset oil temperature prediction model, the predicted oil temperature data T of the target transformer is obtained by iterative calculation in the form of a differential equation p Calculating target oil temperature data T 1 And predicted oil temperature data T p The difference between them results in second difference data (T 1 -T p ) Calculating second difference data and predicted oil temperature data T p Obtain oil temperature error data H by ratio of (2) 2 I.e. H 2 ＝(T 1 -T p )/T p . Determining oil temperature error data H 2 Whether or not the predicted overrun threshold R is reached 2 If H 2 Greater than or equal to R 2 And judging that the target transformer has the prediction overrun, and generating the prediction overrun early warning. Wherein the prediction overrun threshold R 2 The method is comprehensively determined according to the type of the transformer, the cooling mode, the oil temperature value and the early warning precision, is not smaller than 5% at the same time, can be set in sections according to the numerical value interval corresponding to the target oil temperature data of the transformer to be target, and can be properly adjusted according to practical experience. Prediction overrun threshold R 2 The values of (2) may refer to the above embodiments, and are not described herein.
In an alternative embodiment, the statistical analysis is performed on the early warning conditions of all transformers in the transformer substation, and the method specifically includes the following steps: each transformer of the transformer substation is set as a target transformer one by one to perform oil temperature early warning detection, and an oil temperature early warning detection result is obtained, wherein the oil temperature early warning detection result comprises at least one of data error early warning, threshold overrun early warning, mutual ratio overrun early warning and prediction overrun early warning; counting the oil temperature early warning detection result of the transformer based on at least one statistical dimension of the model, the cooling mode, the capacity and the environmental temperature of the transformer to obtain an early warning statistical result, wherein the early warning statistical result comprises an early warning type and an early warning frequency corresponding to each statistical dimension; and generating a visual chart according to the early warning statistical result and displaying the visual chart.
In the above embodiment, the oil temperature early warning detection is performed on all transformers in the transformer substation, and the oil temperature early warning detection result obtained by each detection is stored. And according to the model, cooling mode, capacity, ambient temperature and other statistical dimensions of the transformers, the oil temperature early warning detection results are statistically analyzed to respectively obtain early warning types corresponding to the transformers with different models, different cooling modes, different capacities and different ambient temperatures and early warning times corresponding to each early warning type, and early warning statistical results corresponding to various statistical dimensions are obtained, wherein the statistical results can also comprise ordering the transformers according to the early warning times or total early warning times of any statistical dimension, and related personnel can perform key monitoring and maintenance on the transformers with the largest early warning times and can be replaced if necessary. The early warning statistical result can be queried according to any statistical dimension, and a visual chart generated by the early warning statistical result is displayed in response to a query request, so that related personnel can intuitively grasp the oil temperature early warning distribution of the transformer, analyze the abnormal oil temperature rule, construct a transformer maintenance strategy and timely eliminate hidden danger causing abnormal oil temperature.
Further, as a specific implementation of the method shown in fig. 1, this embodiment provides a device for early warning of abnormal oil temperature of transformer, as shown in fig. 2, where the device includes: the system comprises a data error early warning module 31, a threshold overrun early warning module 32, a mutual ratio overrun early warning module 33 and a prediction overrun early warning module 34.
The data error early warning module 31 is configured to obtain target oil temperature data of a target transformer, determine whether the target oil temperature data is in error, and if yes, generate a data error early warning;
the threshold overrun early warning module 32 is configured to determine whether the target oil temperature data reaches a basic overrun threshold, and if yes, generate a threshold overrun early warning;
the cross ratio overrun early warning module 33 is configured to obtain oil temperature data of the reference transformer to obtain reference oil temperature data, determine whether the target oil temperature data reaches a cross ratio overrun threshold according to the reference oil temperature data, and if yes, generate a cross ratio overrun early warning;
the predicted overrun early warning module 34 is configured to calculate predicted oil temperature data of the target transformer using a preset oil temperature prediction model, determine whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if yes, generate a predicted overrun early warning;
In a specific application scenario, the data error early warning module 31 may be specifically configured to determine whether the oil temperature data meets a data verification condition, where the data verification condition is any one of null, zero, and negative number of the oil temperature data; if the data verification condition is met, determining that the oil temperature data is wrong; if the data verification condition is not met, the oil temperature data is determined to be correct.
In a specific application scenario, the threshold overrun early warning module 32 may be specifically configured to obtain a cooling mode of the target transformer; if the target oil temperature data is greater than or equal to a first basic overrun threshold corresponding to the cooling mode, generating a first-level threshold overrun early warning; if the target oil temperature data is larger than a second basic overrun threshold corresponding to the cooling mode and smaller than the first basic overrun threshold, or the target oil temperature data is equal to the second basic overrun threshold, generating a second-level threshold overrun early warning; wherein the first base overrun threshold is greater than the second base overrun threshold.
In a specific application scenario, the mutual ratio overrun early warning module 33 may be specifically configured to obtain a model, a capacity and a cooling mode of each transformer of a transformer substation where the target transformer is located, and determine whether a similar transformer with the same model, capacity and cooling mode as those of the target transformer exists in the transformer substation; if at least one similar transformer exists, load current and rated current of the target transformer and each similar transformer are obtained, and average load rates of the target transformer and each similar transformer in the current time period are calculated according to the load current and the rated current; obtaining a target load rate according to the average load rate of the target transformer; calculating the average value of the average load rates of the target transformer and each similar transformer to obtain a comparison load rate; and calculating the difference between the target load rate and the comparison load rate to obtain a load rate difference value, and if the absolute value of the load rate difference value is smaller than a load rate difference threshold value, setting the similar transformers as comparison transformers for mutual ratio analysis.
In a specific application scenario, the cross ratio overrun early warning module 33 may be specifically further configured to obtain reference oil temperature data of each reference transformer, calculate an average value of the target oil temperature data and the reference oil temperature data, and obtain average oil temperature data; calculating the difference between the target oil temperature data and the average oil temperature data to obtain first difference data, and obtaining oil temperature mutual difference data according to the ratio between the first difference data and the average oil temperature data; determining a numerical interval corresponding to the target oil temperature data; and if the oil temperature mutual difference data is larger than or equal to the mutual ratio overrun threshold corresponding to the numerical interval, generating a mutual ratio overrun early warning.
In a specific application scenario, the prediction overrun early warning module 34 may be specifically configured to obtain a load current, a rated current and an ambient temperature of the target transformer, input the load current, the rated current and the ambient temperature to an oil temperature prediction model, and calculate predicted oil temperature data of the target transformer by using the oil temperature prediction model; calculating a difference value between the target oil temperature data and the predicted oil temperature data to obtain second difference value data, and obtaining oil temperature error data according to a ratio between the second difference value data and the predicted oil temperature data; determining a numerical interval corresponding to the target oil temperature data; and if the oil temperature error data is greater than or equal to the predicted overrun threshold corresponding to the numerical interval, generating predicted overrun early warning.
In a specific application scenario, the device further comprises an early warning statistics module 35, wherein the early warning statistics module 35 is specifically configured to set each transformer of the transformer substation as a target transformer one by one to perform oil temperature early warning detection, so as to obtain an oil temperature early warning detection result, and the oil temperature early warning detection result comprises at least one of data error early warning, threshold value overrun early warning, mutual ratio overrun early warning and prediction overrun early warning; counting the oil temperature early warning detection result of the transformer based on at least one statistical dimension of the model, the cooling mode, the capacity and the environmental temperature of the transformer to obtain an early warning statistical result, wherein the early warning statistical result comprises an early warning type and an early warning frequency corresponding to each statistical dimension; and generating a visual chart according to the early warning statistical result and displaying the visual chart.
It should be noted that, other corresponding descriptions of each functional unit related to the transformer oil temperature abnormality early warning device provided in this embodiment may refer to corresponding descriptions in fig. 1, and are not repeated here.
Based on the method shown in fig. 1, correspondingly, the embodiment also provides a storage medium, on which a computer program is stored, and the program is executed by a processor to implement the method for early warning of abnormal transformer oil temperature shown in fig. 1.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, where the software product to be identified may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disc, a mobile hard disk, etc.), and include several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to execute the method described in each implementation scenario of the present application.
Based on the method shown in fig. 1 and the embodiment of the transformer oil temperature abnormality pre-warning device shown in fig. 2, in order to achieve the above objective, as shown in fig. 3, the embodiment further provides a computer device for pre-warning of transformer oil temperature abnormality, which may specifically be a personal computer, a server, a smart phone, a tablet computer, a smart watch, or other network devices, etc., where the computer device includes a storage medium and a processor; a storage medium storing a computer program and an operating system; a processor for executing a computer program to implement the method as described above and shown in fig. 1.
Optionally, the computer device may further include an internal memory, a communication interface, a network interface, a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, a Display screen (Display), an input device such as a Keyboard (Keyboard), and the like, and optionally, the communication interface may further include a USB interface, a card reader interface, and the like. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), etc.
It will be appreciated by those skilled in the art that the structure of the computer device for early warning of abnormal transformer oil temperature provided in this embodiment is not limited to the computer device, and may include more or fewer components, or may combine some components, or may be arranged with different components.
The storage medium may also include an operating system, a network communication module. The operating system is a program for managing the hardware of the computer device and the software resources to be identified, and supports the operation of the information processing program and other software and/or programs to be identified. The network communication module is used for realizing communication among all components in the storage medium and communication with other hardware and software in the information processing computer equipment.
From the above description of the embodiments, it will be apparent to those skilled in the art that the present application may be implemented by means of software plus necessary general hardware platforms, or may be implemented by hardware. By applying the technical scheme, whether the oil temperature meter and the signal transmission loop have problems or not can be identified by determining whether oil temperature data are wrong, if so, data error early warning is generated, and transformer oil temperature monitoring vacuum is avoided; the transformer with excessively high oil temperature can be found in advance to a greater extent through threshold overrun early warning so as to strive for the time of sufficient inspection and maintenance; the transformer with the problems of improper cooler investment strategy, low cooler efficiency, self fault and the like can be identified by the mutual ratio overrun early warning and the predictive overrun early warning. Compared with the prior art, the transformer oil temperature detection device has the advantages that the transformer oil temperature can be detected in a plurality of modes, and the transformer with abnormal oil temperature can be timely and accurately identified, so that early warning can be timely sent out, and related personnel can be prompted to maintain safe and stable operation of the transformer.
Those skilled in the art will appreciate that the drawings are merely schematic illustrations of one preferred implementation scenario, and that the modules or flows in the drawings are not necessarily required to practice the present application. Those skilled in the art will appreciate that modules in an apparatus in an implementation scenario may be distributed in an apparatus in an implementation scenario according to an implementation scenario description, or that corresponding changes may be located in one or more apparatuses different from the implementation scenario. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The foregoing application serial numbers are merely for description, and do not represent advantages or disadvantages of the implementation scenario. The foregoing disclosure is merely a few specific implementations of the present application, but the present application is not limited thereto and any variations that can be considered by a person skilled in the art shall fall within the protection scope of the present application.
Claims (10)
1. The method for early warning of abnormal oil temperature of the transformer is characterized by comprising the following steps:
acquiring target oil temperature data of a target transformer, determining whether the target oil temperature data is wrong, and if so, generating a data error early warning; if not, executing the following steps:
determining whether the target oil temperature data reaches a basic overrun threshold value, if so, generating threshold overrun early warning;
Obtaining oil temperature data of a comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a cross ratio overrun threshold according to the comparison oil temperature data, and if so, generating a cross ratio overrun early warning;
and calculating predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating a predicted overrun early warning.
2. The method of claim 1, wherein said determining whether said target oil temperature data is erroneous comprises:
determining whether the oil temperature data meets a data verification condition, wherein the data verification condition is any one of null, zero and negative number of the oil temperature data;
if the data verification condition is met, determining that the oil temperature data is wrong;
and if the data verification condition is not met, determining that the oil temperature data is error-free.
3. The method of claim 1, wherein determining whether the target oil temperature data reaches a base overrun threshold, and if so, generating a threshold overrun warning, comprises:
obtaining a cooling mode of the target transformer;
If the target oil temperature data is greater than or equal to a first basic overrun threshold corresponding to the cooling mode, generating a first-level threshold overrun early warning;
if the target oil temperature data is larger than a second basic overrun threshold corresponding to the cooling mode and smaller than the first basic overrun threshold, or the target oil temperature data is equal to the second basic overrun threshold, generating a second-level threshold overrun early warning;
wherein the first base overrun threshold is greater than the second base overrun threshold.
4. The method of claim 1, wherein prior to the obtaining the oil temperature data of the reference transformer to obtain reference oil temperature data, determining from the reference oil temperature data whether the target oil temperature data reaches a cross-ratio overrun threshold, the method further comprises:
obtaining the model, capacity and cooling mode of each transformer of a transformer station where the target transformer is located, and determining whether similar transformers with the same model, capacity and cooling mode as those of the target transformer exist in the transformer station;
if at least one similar transformer exists, load current and rated current of the target transformer and each similar transformer are obtained, and average load rates of the target transformer and each similar transformer in a current time period are calculated according to the load current and the rated current;
Obtaining a target load rate according to the average load rate of the target transformer;
calculating the average value of the average load rates of the target transformer and each similar transformer to obtain a comparison load rate;
and calculating the difference between the target load rate and the comparison load rate to obtain a load rate difference value, and if the absolute value of the load rate difference value is smaller than a load rate difference threshold value, setting the similar transformers as the comparison transformers for mutual ratio analysis.
5. The method according to claim 1 or 4, wherein the obtaining the oil temperature data of the reference transformer obtains reference oil temperature data, and determining whether the target oil temperature data reaches a cross ratio overrun threshold according to the reference oil temperature data, and if so, generating a cross ratio overrun early warning, includes:
obtaining reference oil temperature data of each reference transformer, and calculating the average value of the target oil temperature data and the reference oil temperature data to obtain average oil temperature data;
calculating the difference value between the target oil temperature data and the average oil temperature data to obtain first difference value data, and obtaining oil temperature mutual difference data according to the ratio between the first difference value data and the average oil temperature data;
Determining a numerical interval corresponding to the target oil temperature data;
and if the oil temperature mutual difference data is larger than or equal to the mutual ratio overrun threshold value corresponding to the numerical interval, generating a mutual ratio overrun early warning.
6. The method according to claim 1, wherein calculating the predicted oil temperature data of the target transformer using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a predicted overrun threshold according to the predicted oil temperature data, and if so, generating a predicted overrun early warning, includes:
the load current, rated current and environmental temperature of the target transformer are obtained and input into the oil temperature prediction model, and the oil temperature prediction model is utilized to calculate and obtain predicted oil temperature data of the target transformer;
calculating the difference value between the target oil temperature data and the predicted oil temperature data to obtain second difference value data, and obtaining oil temperature error data according to the ratio between the second difference value data and the predicted oil temperature data;
determining a numerical interval corresponding to the target oil temperature data;
and if the oil temperature error data is greater than or equal to the prediction overrun threshold corresponding to the numerical value interval, generating a prediction overrun early warning.
7. The method according to claim 1, wherein the method further comprises:
each transformer of the transformer substation is set as a target transformer one by one to perform oil temperature early warning detection, and an oil temperature early warning detection result is obtained, wherein the oil temperature early warning detection result comprises at least one of data error early warning, threshold overrun early warning, mutual ratio overrun early warning and prediction overrun early warning;
counting the oil temperature early warning detection result of the transformer based on at least one statistical dimension of the model, the cooling mode, the capacity and the environmental temperature of the transformer to obtain an early warning statistical result, wherein the early warning statistical result comprises an early warning type and an early warning frequency corresponding to each statistical dimension;
and generating a visual chart according to the early warning statistical result and displaying the visual chart.
8. An abnormal transformer oil temperature early warning device, which is characterized by comprising:
the data error early warning module is used for acquiring target oil temperature data of a target transformer, determining whether the target oil temperature data is in error or not, and if so, generating data error early warning;
the threshold overrun early warning module is used for determining whether the target oil temperature data reach a basic overrun threshold or not, and if yes, generating threshold overrun early warning;
The mutual ratio overrun early warning module is used for acquiring the oil temperature data of the comparison transformer to obtain comparison oil temperature data, determining whether the target oil temperature data reaches a mutual ratio overrun threshold value according to the comparison oil temperature data, and if so, generating a mutual ratio overrun early warning;
and the prediction overrun early warning module is used for calculating and obtaining the predicted oil temperature data of the target transformer by using a preset oil temperature prediction model, determining whether the target oil temperature data reaches a prediction overrun threshold value according to the predicted oil temperature data, and if so, generating the prediction overrun early warning.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method of any of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor implements the steps of the method according to any one of claims 1 to 7.
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