CN117250563A - Method for predicting insulation life of transformer oil - Google Patents
Method for predicting insulation life of transformer oil Download PDFInfo
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- CN117250563A CN117250563A CN202311105346.3A CN202311105346A CN117250563A CN 117250563 A CN117250563 A CN 117250563A CN 202311105346 A CN202311105346 A CN 202311105346A CN 117250563 A CN117250563 A CN 117250563A
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- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000009413 insulation Methods 0.000 title claims abstract description 29
- YLQBMQCUIZJEEH-UHFFFAOYSA-N Furan Chemical compound C=1C=COC=1 YLQBMQCUIZJEEH-UHFFFAOYSA-N 0.000 claims abstract description 64
- 239000003921 oil Substances 0.000 claims description 143
- 230000032683 aging Effects 0.000 claims description 19
- 238000004804 winding Methods 0.000 claims description 12
- 239000002480 mineral oil Substances 0.000 claims description 10
- 235000010446 mineral oil Nutrition 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000010438 heat treatment Methods 0.000 claims description 6
- 239000013307 optical fiber Substances 0.000 claims description 5
- 238000011897 real-time detection Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 4
- 230000015556 catabolic process Effects 0.000 claims description 3
- 238000006731 degradation reaction Methods 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 3
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 238000004590 computer program Methods 0.000 description 7
- 230000008901 benefit Effects 0.000 description 5
- 238000001514 detection method Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000010779 crude oil Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005194 fractionation Methods 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- 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
-
- 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
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1281—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of liquids or gases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/04—Ageing analysis or optimisation against ageing
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Power Engineering (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Housings And Mounting Of Transformers (AREA)
Abstract
The invention relates to the technical field of insulation life prediction in power equipment, in particular to a method for predicting the insulation life of transformer oil. Comprising the following steps: detecting the hot spot temperature of transformer oil; predicting the DP value in the transformer oil through the furan content; calculating the pollution index of the transformer oil; calculating the dielectric constant of the brand new transformer oil; the dielectric constant attenuation value of the transformer oil is predicted by combining the dielectric constant of the brand-new transformer oil; obtaining the predicted service life and the replacement time of the transformer oil through comparison; re-evaluating at fixed intervals; and counting various transformer types and transformer oil by using the big data. According to the invention, the replacement life of the transformer oil is predicted by combining various transformer operation state parameters, so that the situation that the replacement is not timely influenced the service life of the transformer is avoided; instructive work is being done for the later use of transformers and replacement of transformer oil.
Description
Technical Field
The invention relates to the technical field of insulation life prediction in power equipment, in particular to a method for predicting the insulation life of transformer oil.
Background
With the development of the power grid, the development of electric energy is also more and more important in the country, a transformer is very important electrical equipment, and the transformer is also the most important component in the power system. In other words, once a transformer fails severely, our power consumer is greatly affected. And some industries that rely on electricity also result in economic losses. Once this happens, it is a loss for the people of the country.
Transformer oil, as the most important insulating component in transformer insulation, will age severely resulting in a transformer that is not used for long periods of time, which will result in economic losses in replacing new transformers and in compromising the stability of the power system. And also gives the power consumer a poor experience. Therefore, the replacement time of the transformer oil influences the use benefit and service life of the transformer. It is very interesting for the power industry to predict the replacement time.
Mineral oil refers to a mixture of refined liquid hydrocarbons obtained from petroleum, crude oil is subjected to normal pressure and reduced pressure fractionation, solvent extraction and dewaxing, and hydrofining, and the corresponding mineral oil can be aged due to the increase of the service life of a transformer, once the mineral oil is aged, the transformer can have insulation faults, and once the mineral oil is aged, the dielectric strength of the mineral oil can be seriously reduced, the insulation effect is not played any more, and the working performance of the transformer is seriously affected. Therefore, it is important to keep good quality of mineral oil, so that not only real-time detection is needed, but also prediction of the life of the mineral oil is needed in advance, so that the transformer oil can be replaced more accurately and effectively, and loss caused by insulation faults of the transformer is prevented. In view of this, we propose a method for predicting the insulation life of transformer oil.
Disclosure of Invention
The invention aims to provide a method for predicting the insulation life of transformer oil, which aims to solve the problems in the prior art.
In order to solve the technical problems, one of the purposes of the invention is to provide a method for predicting the insulation life of transformer oil, which is based on real-time detection of a transformer and comparison between pollution index and furan content and DP value of the transformer oil to obtain more accurate transformer oil state prediction, and utilizes big data to integrate to achieve accurate prediction of the dielectric constant of the transformer oil; predicting the replacement life of the transformer oil by combining various transformer operation state parameters, and reevaluating the fixed time to be closer to the actual transformer oil replacement time; the method has the advantages that a worker can more accurately and approximately estimate the replacement of the transformer oil in advance, and the situation that the service life of the transformer is influenced due to untimely replacement is avoided; the method specifically comprises the following steps:
s1, detecting the hot spot temperature of transformer oil by using an optical fiber sensor at room temperature, and detecting the current of the transformer when the transformer is fully loaded; the temperature DP of the windings at 55 degrees and 110 degrees under rated load is measured by an optical fiber sensor aiming at the windings;
s2, predicting the furan content in the transformer oil approximately according to the data measured before, predicting the DP value in the transformer oil according to the furan content, and setting the lower limit of the DP value as the replacement transformer oil age by taking the DP value as a standard;
s3, calculating the pollution index of the transformer oil at the moment by combining the obtained predicted furan content with the temperature of the winding under two rated load operation, and obtaining the pollution condition of the transformer oil at the moment;
s4, testing brand-new mineral oil which does not generate aging products at room temperature, and obtaining a dielectric constant A of brand-new transformer oil by using a dielectric constant sensor;
s5, predicting the dielectric constant attenuation multiple of the transformer oil according to the predicted value of the furan content and the predicted value of the pollution index, combining the dielectric constant A of the brand-new transformer oil, predicting the dielectric constant attenuation value of the transformer oil, setting a lower limit attenuation value, and if the attenuation value is reached, replacing the transformer oil in time;
s6, comparing the calculated age according to the dielectric constant attenuation value with the calculated replacement age of the DP value lower limit, and selecting a time period with an earlier replacement age; further obtaining the predicted service life and the replacement time of the transformer oil;
s7, reevaluating the service life of the transformer oil at fixed intervals, and updating the predicted value to obtain more accurate predicted time;
and S8, counting various transformer types and transformer oil by utilizing big data to obtain the average replacement life of various transformer oil so as to have more sufficient preparation time and expectation for the replacement of the transformer oil. Preventing economic loss caused by untimely replacement.
As a further improvement of the technical scheme, in the step S1, various state indexes of the transformer are detected at room temperature, wherein the heating factor of the transformer is calculated by using the full load current and the hot spot temperature, and the winding temperatures of 55 degrees and 110 degrees are measured when the transformer is loaded to obtain the aging factor of the transformer oil.
As a further improvement of the present technical solution, in the step S2, the furan content of the transformer is predicted and the DP value is calculated, where:
the predictive formula for furan content is:
wherein b is a heating factor of transformer oil, and t is the service life of the transformer oil;
the calculation formula of the DP value is as follows:
wherein FAL is furan content, and the upper and lower limits of DP value are 100-200, and can be regulated according to actual practice.
As a further improvement of the present technical solution, in the step S3, the pollution index is calculated, specifically:
the pollution index is calculated by combining the predicted value of the furan content and the ageing factor, and the purpose of the pollution index is to describe the state of the transformer oil at the moment; during the use process of the transformer, the transformer oil can decompose a large number of ageing characteristics; the pollution index is a description of the above states;
the calculation formula is as follows:
D＝F(t)+aC(t) (3)
wherein C (t) is an aging factor, a is a relative factor, and 0.42 is taken;
the formula for calculating the aging factor is:
where h110 and h55 are the temperatures measured at the load temperatures of 110 degrees and 55 degrees, respectively.
As a further improvement of the technical scheme, in the step S5, the transformer oil attenuation value is required to be calculated more accurately, and the initial dielectric constant of the transformer oil is required to be calculated, that is, the initial dielectric constant of the transformer oil is detected by using the dielectric constant sensor in the step S4, so as to obtain the initial value a.
As a further improvement of the technical scheme, in the step S5, the dielectric constant attenuation of the transformer oil is calculated by using the furan content and the pollution index, and the calculation formula is as follows:
H＝A×(e (-D/X) ) (5)
wherein A is the original dielectric constant, X is the dielectric degradation coefficient, and depends on the load current; the dielectric constant attenuation value is 60% of the initial value, namely H is less than or equal to 0.6A, and once the predicted value reaches the early warning value, the predicted replacement period of the transformer oil is t at the moment.
As a further improvement of the technical scheme, in the step S6, the DP value and the dielectric constant can be used for judging indexes of the replacement life of the transformer oil, and the two predicted replacement ages of the transformer oil are compared, so that the replacement life of the transformer oil is preferentially selected, and a more accurate service life prediction effect is achieved.
As a further improvement of the technical scheme, in the step S7, state detection is performed on the transformer oil at fixed intervals, so that more accurate prediction years can be achieved.
As a further improvement of the technical scheme, in the step S8, average statistics is performed on various transformer models and oil to obtain a better predicted replacement period, so that guiding work can be performed for using the transformer and replacing transformer oil in the future.
Another object of the present invention is to provide an apparatus for predicting the insulation life of transformer oil, comprising a processor, a memory and a computer program stored in the memory and running on the processor, the processor being adapted to implement the steps of the above method for predicting the insulation life of transformer oil when the computer program is executed.
It is a fourth object of the present invention to provide a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the above-described method of predicting the insulation life of transformer oil.
Compared with the prior art, the invention has the beneficial effects that:
1. in the method for predicting the insulation life of the transformer oil, the transformer oil replacement life is predicted by combining a plurality of transformer running state parameters based on real-time detection of the transformer and comparison between the pollution index, the furan content and the DP value of the transformer oil to obtain more accurate transformer oil state prediction, and the transformer oil replacement life is reevaluated for a fixed time to be closer to the actual transformer oil replacement time;
2. in the method for predicting the insulation life of the transformer oil, big data are utilized to integrate to accurately predict the dielectric constant of the transformer oil; the method has the advantages that a worker can more accurately and approximately estimate the replacement of the transformer oil in advance, and the situation that the service life of the transformer is influenced due to untimely replacement is avoided; instructive work can also be done for the later use of transformers and replacement of transformer oil.
Drawings
FIG. 1 is a flow chart of an exemplary method of the present invention;
fig. 2 is a block diagram of an exemplary electronic computer device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the embodiment provides a method for predicting the insulation life of transformer oil, which is based on real-time detection of a transformer and comparison between pollution index and furan content and DP value of transformer oil to obtain more accurate transformer oil state prediction, and utilizes big data to integrate to achieve accurate prediction of the dielectric constant of the transformer oil; predicting the replacement life of the transformer oil by combining various transformer operation state parameters, and reevaluating the fixed time to be closer to the actual transformer oil replacement time; the method has the advantages that a worker can more accurately and approximately estimate the replacement of the transformer oil in advance, and the situation that the service life of the transformer is influenced due to untimely replacement is avoided; the method specifically comprises the following steps.
S1, detecting a running transformer at room temperature, detecting the hot spot temperature of transformer oil by using a sensor, and detecting the current of the transformer when the transformer is fully loaded; the temperature DP values of the windings at 55 degrees and 110 degrees under rated load are measured by a sensor aiming at the windings, so as to obtain the ageing factor of the transformer oil; the sensors used here are all optical fiber sensors, which are widely used in measuring winding temperature; the method is to solve the aging factor and the heating factor of the transformer oil, record the detection data in the form of an average value and calculate the formula.
S2, after the data are measured in the step S1 and an average value is obtained, the furan content in the transformer oil is calculated and predicted according to the average value, the DP value in the transformer oil is predicted according to the furan content, the lower limit of the DP value is set as the transformer oil replacement limit according to the average value, the lower limit of the DP value is usually 150 to 200, once the preset value is reached, the transformer oil cannot be used any more, personnel are required to replace the transformer oil in time, and the predicted time is recorded.
In the step, the furan content of the transformer is predicted and the DP value is calculated, wherein:
the predictive formula for furan content is:
wherein b is a heating factor of transformer oil, and t is the service life of the transformer oil;
the calculation formula of the DP value is as follows:
wherein FAL is furan content, and the upper and lower limits of DP value are 100-200, and can be regulated according to actual practice.
S3, calculating the pollution index of the transformer oil at the moment by combining the obtained predicted furan content with the temperature of the winding under two rated load operation, and obtaining the pollution condition and the pollution index of the transformer oil at the moment; the pollution index is an index for judging the pollution degree of the transformer oil, and the obtained index is recorded.
In this step, the pollution index is calculated, specifically:
the pollution index is calculated by combining the predicted value of the furan content and the ageing factor, and the purpose of the pollution index is to describe the state of the transformer oil at the moment; during the use process of the transformer, the transformer oil can decompose a large number of ageing characteristics; the pollution index is a description of the above states;
the calculation formula is as follows:
D＝F(t)+aC(t) (3)
wherein C (t) is an aging factor, a is a relative factor, and 0.42 is taken;
the formula for calculating the aging factor is:
where h110 and h55 are the temperatures measured at the load temperatures of 110 degrees and 55 degrees, respectively.
S4, obtaining brand-new oil samples of experimental transformers through other ways, testing brand-new mineral oil which does not generate aging products at room temperature, and obtaining the dielectric constant A of the brand-new transformer oil by using the DC-OL dielectric constant sensor.
S5, predicting the dielectric constant attenuation multiple of the transformer oil according to the predicted value of the furan content and the predicted value of the pollution index, combining the dielectric constant A of the brand-new transformer oil, predicting the dielectric constant attenuation value of the transformer oil, setting a lower limit attenuation value, and if the attenuation value is reached, replacing the transformer oil in time;
in this step, to calculate the attenuation value of the transformer oil more accurately, the initial dielectric constant of the transformer oil needs to be calculated, that is, the initial dielectric constant of the transformer oil is detected by using the dielectric constant sensor in step S4, so as to obtain the initial value a.
Specifically, the furan content and the pollution index are used for calculating the dielectric constant attenuation of the transformer oil, and the calculation formula is as follows:
H＝A×(e (-D/X) ) (5)
wherein A is the original dielectric constant, X is the dielectric degradation coefficient, and depends on the load current; the dielectric constant attenuation value is 60% of the initial value, namely H is less than or equal to 0.6A, and once the predicted value reaches the early warning value, the predicted replacement period of the transformer oil is t at the moment.
S6, comparing the calculated age according to the dielectric constant attenuation value with the calculated replacement age of the DP value lower limit, and selecting a time period with an earlier replacement age; further obtaining the predicted service life and the replacement time of the transformer oil;
the DP value and the dielectric constant can be used for judging indexes of the replacement life of the transformer oil, and the two predicted replacement life of the transformer oil are compared, so that the replacement life of the transformer oil is preferentially selected, and a more accurate service life prediction effect is achieved.
S7, reevaluating the service life of the transformer oil at fixed intervals, and updating the predicted value to obtain more accurate predicted time; the state detection is carried out on the transformer oil at fixed intervals, so that more accurate prediction years can be achieved.
S8, finally, summarizing the obtained data, and counting various transformer types and transformer oil by utilizing the big data to obtain the average replacement life of various transformer oil so as to have more sufficient preparation time and expectation for the replacement of the transformer oil; the economic loss caused by untimely replacement is prevented; instructive work can also be done for the later use of transformers and replacement of transformer oil.
As shown in fig. 2, the present embodiment also provides an apparatus for predicting the insulation life of transformer oil, the apparatus comprising a processor, a memory, and a computer program stored in the memory and running on the processor.
The processor comprises one or more processing cores, the processor is connected with the memory through a bus, the memory is used for storing program instructions, and the steps of the method for predicting the insulation life of the transformer oil are realized when the processor executes the program instructions in the memory.
Alternatively, the memory may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
In addition, the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the method for predicting the insulation life of the transformer oil when being executed by a processor.
Optionally, the invention also provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the steps of the method of predicting the insulation life of transformer oil in the above aspects.
It will be appreciated by those of ordinary skill in the art that the processes for implementing all or part of the steps of the above embodiments may be implemented by hardware, or may be implemented by a program for instructing the relevant hardware, and the program may be stored in a computer readable storage medium, where the above storage medium may be a read-only memory, a magnetic disk or optical disk, etc.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. The method is based on real-time detection of a transformer and comparison between pollution index and furan content and DP value of transformer oil to obtain more accurate transformer oil state prediction; the method is characterized in that: predicting the replacement life of transformer oil by combining various transformer operation state parameters; the method specifically comprises the following steps:
s1, detecting the hot spot temperature of transformer oil by using an optical fiber sensor at room temperature, and detecting the current of the transformer when the transformer is fully loaded; the temperature DP of the windings at 55 degrees and 110 degrees under rated load is measured by an optical fiber sensor aiming at the windings;
s2, predicting the furan content in the transformer oil approximately according to the data measured before, predicting the DP value in the transformer oil according to the furan content, and setting the lower limit of the DP value as the replacement transformer oil age by taking the DP value as a standard;
s3, calculating the pollution index of the transformer oil at the moment by combining the obtained predicted furan content with the temperature of the winding under two rated load operation, and obtaining the pollution condition of the transformer oil at the moment;
s4, testing brand-new mineral oil which does not generate aging products at room temperature, and obtaining the dielectric constant of brand-new transformer oil by using a dielectric constant sensor;
s5, predicting the dielectric constant attenuation multiple of the transformer oil according to the predicted value of the furan content and the predicted value of the pollution index, combining the dielectric constant of the brand-new transformer oil, predicting the dielectric constant attenuation value of the transformer oil, setting a lower limit attenuation value, and if the attenuation value is reached, replacing the transformer oil in time;
s6, comparing the calculated age according to the dielectric constant attenuation value with the calculated replacement age of the DP value lower limit, and selecting a time period with an earlier replacement age; further obtaining the predicted service life and the replacement time of the transformer oil;
s7, reevaluating the service life of the transformer oil at fixed intervals, and updating the predicted value to obtain more accurate predicted time;
and S8, counting various transformer types and transformer oil by utilizing big data to obtain the average replacement life of various transformer oil so as to have more sufficient preparation time and expectation for the replacement of the transformer oil.
2. The method for predicting the insulation life of transformer oil as recited in claim 1, wherein: in the step S1, various state indexes of the transformer are detected at room temperature, wherein the heating factor of the transformer is calculated by using the full load current and the hot spot temperature, and the winding temperatures of 55 degrees and 110 degrees are measured when the transformer is loaded to obtain the aging factor of the transformer oil.
3. The method for predicting the insulation life of transformer oil according to claim 2, wherein: in the step S2, the furan content of the transformer is predicted and the DP value is calculated, wherein:
the predictive formula for furan content is:
wherein b is a heating factor of transformer oil, and t is the service life of the transformer oil;
the calculation formula of the DP value is as follows:
wherein FAL is furan content, and the upper and lower limits of DP value are 100-200, and can be regulated according to actual practice.
4. A method of predicting the insulation life of transformer oil as recited in claim 3, wherein: in the step S3, the pollution index is calculated, which specifically includes:
the pollution index is calculated by combining the predicted value of the furan content and the ageing factor, and the purpose of the pollution index is to describe the state of the transformer oil at the moment; during the use process of the transformer, the transformer oil can decompose a large number of ageing characteristics; the pollution index is a description of the above states;
the calculation formula is as follows:
D＝F(t)+aC(t) (3)
wherein C (t) is an aging factor, and a is a relative factor;
the formula for calculating the aging factor is:
where h110 and h55 are the temperatures measured at the load temperatures of 110 degrees and 55 degrees, respectively.
5. The method for predicting the insulation life of transformer oil of claim 4, wherein: in the step S5, to calculate the attenuation value of the transformer oil more accurately, the initial dielectric constant of the transformer oil needs to be calculated, that is, the initial dielectric constant of the transformer oil is detected by using the dielectric constant sensor in the step S4, so as to obtain the initial value a.
6. The method for predicting the insulation life of transformer oil of claim 5, wherein: in the step S5, the dielectric constant attenuation of the transformer oil is calculated by using the furan content and the pollution index, and the calculation formula is as follows:
H＝A×(e(-D/XQ)(5)
where A is the original dielectric constant, and X is the dielectric degradation coefficient, depending on the load current.
7. The method of predicting the insulation life of transformer oil of claim 6, wherein: in the step S6, the DP value and the permittivity may be used to determine the index of the replacement life of the transformer oil, and the two predicted replacement life of the transformer oil are compared, so as to preferentially select the replacement life of the transformer oil, so as to achieve a more accurate service life prediction effect.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311105346.3A CN117250563A (en) | 2023-08-30 | 2023-08-30 | Method for predicting insulation life of transformer oil |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311105346.3A CN117250563A (en) | 2023-08-30 | 2023-08-30 | Method for predicting insulation life of transformer oil |
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| CN117250563A true CN117250563A (en) | 2023-12-19 |
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| CN202311105346.3A Pending CN117250563A (en) | 2023-08-30 | 2023-08-30 | Method for predicting insulation life of transformer oil |
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