Hot spot temperature detection method based on transformer temperature field distribution calculation

Abstract

The invention discloses a hot spot temperature detection method based on transformer temperature field distribution calculation, and relates to the technical field of transformer detection. According to the method, historical operation data in a set time window before a current time point of the transformer is extracted, the historical operation data and current operation data are comprehensively evaluated to determine initial temperature distribution, the load rate, the environment temperature and the operated duration are converted into a load score, a temperature score and an operation score respectively, weighted calculation is carried out according to a formula, and the temperature of the transformer is calculated. And the initial temperature distribution of the historical data with the lowest similar index is selected as the current initial temperature distribution, so that the initial temperature is more practical, and the subsequent calculation deviation is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer detection, and specifically to a hot spot temperature detection method based on the calculation of the transformer temperature field distribution. Background Technique

[0002] As a key device in the power system, the operating state of the transformer directly affects the safety and stability of the power system. The hot spot temperature is an important indicator for evaluating the operating condition of the transformer. An excessive hot spot temperature will accelerate the insulation aging, shorten the service life of the transformer, and even cause failures.

[0003] At present, the traditional hot spot temperature detection method still has the following deficiencies in the actual application process: It fails to fully consider the complex physical structure and dynamic operating conditions inside the transformer, and determine the temperature distribution by combining historical data, resulting in a large difference between the calculation result and the actual hot spot temperature, and unable to provide an accurate basis for the operation and maintenance of the transformer; In addition, it does not combine the winding data, magnetic permeability data, and cooling oil data during the actual operation of the transformer, and then adjust and optimize the temperature distribution of each partition, so the accuracy of hot spot temperature detection cannot be guaranteed.

[0004] Therefore, a hot spot temperature detection method based on the calculation of the transformer temperature field distribution is introduced. Summary of the Invention

[0005] The purpose of the present invention is to solve the problems pointed out in the background technique, and propose a hot spot temperature detection method based on the calculation of the transformer temperature field distribution.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A hot spot temperature detection method based on the calculation of the transformer temperature field distribution, including: Determine the initial conditions: Extract the historical operation data of the transformer within a set time window before the current time point; and conduct a comprehensive evaluation with the operation data of the transformer at the current time point to determine the initial temperature distribution of the transformer at the current time point; where the operation data includes the load rate, ambient temperature, and the operating duration. Evaluate and correct: Based on the initial temperature distribution of the transformer at the current time point, divide the transformer temperature field into a winding area, a core area, and a cooling medium area and conduct a comprehensive evaluation respectively, and make a secondary adjustment to the initial temperature distribution of the transformer according to the results of the comprehensive evaluation, and use it as the final temperature distribution of the corresponding temperature field of the transformer after adjustment.

[0007] As a preferred implementation manner of the present invention, extract the historical operation data of the transformer within a set time window before the current time point; and conduct a comprehensive evaluation with the operation data of the transformer at the current time point, specifically: Extract the load rate, ambient temperature, and operating duration of the transformer at the current time point. Pre - establish the score conversion rules corresponding to the load rate, ambient temperature, and operating duration respectively, and convert the load rate, ambient temperature, and operating duration of the transformer at the current time point into a load score, a temperature score, and an operating score respectively; Mark the load score, temperature score, and operating score of the transformer at the current time point as ; At the same time, extract the historical operation data of the transformer within a set time window before the current time point, and also use the score conversion rules to convert the load rate, ambient temperature, and operating duration in each group of historical operation data into a load score, a temperature score, and an operating score respectively. After conversion, mark the load score, temperature score, and operating score of each group of historical operation data as .

[0008] As a preferred embodiment of the present invention, determine the initial temperature distribution of the transformer at the current time point, specifically: According to the formula Perform weighted calculations on the operation data of the transformer at the current time point and each group of historical operation data to determine the similarity index between the operation data of the transformer at the current time point and each group of historical operation data ; Wherein are the preset weight coefficients corresponding to the load score, temperature score, and operating score respectively; Based on the similarity index between the operation data of the transformer at the current time point and each group of historical operation data, select the historical operation data with the lowest similarity index as the similar historical data of the transformer at the current time point, and use the initial temperature distribution of the similar historical data as the initial temperature distribution of the transformer at the current time point.

[0009] As a preferred embodiment of the present invention, pre - establish the score conversion rules corresponding to the load rate, ambient temperature, and operating duration respectively, specifically: Preset each group of load rate value ranges corresponding to the load rate, and each group of load rate value ranges corresponds to a load score; preset each group of temperature value ranges corresponding to the ambient temperature, and each group of temperature value ranges corresponds to a temperature score; preset each group of operating duration value ranges corresponding to the operating duration, and each group of operating duration value ranges corresponds to an operating score.

[0010] As a preferred embodiment of the present invention, divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct comprehensive evaluations respectively. The specific process of evaluating the cooling medium area is: Obtain the cooling oil flow rate and cooling oil temperature data of the transformer within a set time window after the current time point, and set the flow rate reference value and temperature reference value of the cooling oil when the transformer is operating normally; For the cooling oil flow rate and cooling oil temperature within the set time window, calculate the average value respectively as the flow rate evaluation value and temperature evaluation value, denoted as and ; According to the formula Perform weighted calculation on the flow rate evaluation value and temperature evaluation value of the transformer within the set time window after the current time point to obtain the cooling oil evaluation index of the transformer within the set time window after the current time point; where represent the flow rate reference value and temperature reference value respectively; are the preset weight coefficients corresponding to the flow rate evaluation value and temperature evaluation value respectively. Compare the calculated cooling oil evaluation index with the corresponding preset cooling oil threshold index. If it is higher than the corresponding preset cooling oil threshold index, then calculate the difference between the two and record it as the adjustment difference; Preset the intervals where each group of differences corresponding to the adjustment difference is located. Each group of adjustment differences corresponds to a temperature increase set, and the temperature increase set includes the temperature increase values of each divided area of the transformer.

[0011] As a preferred embodiment of the present invention, divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct comprehensive evaluations respectively. The specific process of evaluating the winding area is as follows: Obtain the winding resistance of the transformer within a set time window after the current time point, and preset the reference resistance value corresponding to the winding resistance; extract the winding resistance at each time point within the set time window as the numerator and the reference resistance value as the denominator, and calculate the ratio respectively to obtain the resistance ratio at each time point within the set time window; After removing one highest resistance ratio and one lowest resistance ratio, calculate the average value of the remaining groups of resistance ratios to obtain the resistance evaluation ratio of the transformer within the set time window after the current time point; Compare the resistance evaluation ratio within the set time window with the preset resistance threshold ratio. If it is higher than the corresponding preset resistance threshold ratio, then calculate the difference between the two and record it as the winding difference; Preset the intervals where each group of differences corresponding to the winding difference is located. Each group of winding differences corresponds to a winding temperature increase value.

[0012] As a preferred embodiment of the present invention, divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct comprehensive evaluations respectively. The specific process of evaluating the iron core area is as follows: Obtain the core permeability of the transformer within a set time window after the current time point, and the reference permeability value corresponding to the preset core permeability; Calculate the average value of the core permeability within the set time window, denoted as the average permeability rate. Then, starting from the current set time window, extract the average permeability rates of the X time windows before the starting point; where X > 3; Calculate the average value of the average permeability rates of the X time windows, denoted as the historical average rate; compare the historical average rate with the average permeability rate of the current set time window. If the average permeability rate of the current set time window is less than the historical average rate, then use the average permeability rate of the current set time window as the denominator and the historical average rate as the numerator for ratio calculation to obtain the magnetic conductance trend ratio of the transformer within the current set time window, denoted as F; Calculate the magnetic conductance evaluation rate W through the formula W = K - K×(F - 1); where K represents the average permeability rate of the current set time window; and compare it with the reference permeability value. If the magnetic conductance evaluation rate is lower than the reference permeability value, then calculate the difference between the two and denote it as the core difference; Preset the intervals where each group of differences corresponding to the core difference is located, and each core difference corresponds to an increase value of the core temperature.

[0013] As a preferred implementation manner of the present invention, perform secondary adjustment on the initial temperature distribution of the transformer according to the comprehensive evaluation result, specifically: Based on the calculated adjustment difference, on the basis of the initial temperature distribution, adjust the temperature of each partition area of the transformer by the corresponding temperature increase value; after adjusting the temperature of each partition area of the transformer by the corresponding temperature increase value, adjust the corresponding winding temperature increase value for the adjusted winding area; after adjusting the temperature of each partition area of the transformer by the corresponding temperature increase value, adjust the corresponding core temperature increase value for the adjusted core area; after the adjustment is completed, it is used as the final temperature distribution of the corresponding temperature field of the transformer.

[0014] As a preferred implementation manner of the present invention, it further includes: Real-time update: According to the preset adjustment time interval, after reaching the preset adjustment time interval, re-determine the initial temperature distribution and the final temperature distribution; Verification and optimization: Apply the final temperature distribution to the pre-constructed transformer temperature field calculation model, and compare it with the temperature measurement data during the actual operation of the transformer; if the comparison result shows that the difference between the calculated temperature and the measured temperature in a certain partition area is higher than the corresponding preset allowable value, then trigger a deviation signal and send it to the technician.

[0015] Compared with the prior art, the beneficial effects of the present invention are: The present invention determines the initial temperature distribution by extracting the historical operation data within a set time window before the current time point of the transformer and comprehensively evaluating it with the current operation data. The load rate, ambient temperature, and operation duration are respectively converted into load scores, temperature scores, and operation scores, and then weighted calculation is performed according to the formula. The initial temperature distribution of the historical data with the lowest proximity index is selected as the current initial temperature distribution, making the initial temperature more in line with the actual situation and reducing subsequent calculation deviations; The present invention evaluates by dividing the transformer temperature field into a winding area, an iron core area, and a cooling medium area respectively. In the cooling medium area, the cooling oil flow rate and temperature data are obtained to calculate the evaluation index, and after comparison with the threshold value, the temperature of each area is adjusted; in the winding area, the temperature is adjusted by calculating the resistance evaluation ratio and comparing it with the threshold value; in the iron core area, the magnetic conductance evaluation rate is calculated based on the change of magnetic permeability and compared with the reference value to adjust the temperature. By comprehensively considering multiple factors in multiple areas, the actual operation state of the transformer is fully reflected, the initial temperature distribution is corrected, and the accuracy of hot spot temperature detection is improved; The present invention re-determines the initial and final temperature distributions at preset adjustment time intervals to ensure that the temperature field distribution can reflect the change of the transformer operation state in real time. The final temperature distribution is applied to the calculation model and compared with the actual measurement data. If there is a deviation, a signaling is triggered to the technician, and the technician evaluates and adjusts it to make the temperature field distribution more accurate. Description of the Drawings

[0016] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the drawings.

[0017] Figure 1 It is a flowchart of the present invention. Detailed Embodiments

[0018] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] Please refer to Figure 1 As shown, a hot spot temperature detection method based on the transformer temperature field distribution includes: Determine the initial conditions: Extract the historical operation data of the transformer within a set time window before the current time point; Obtain the historical operation data from the operation and maintenance management system of the transformer, the monitoring device logs, and the past maintenance reports. These data cover records in different time periods, different seasons, and different operating conditions to ensure the comprehensiveness and diversity of the data; And conduct a comprehensive evaluation with the operation data of the transformer at the current time point to determine the initial temperature distribution of the transformer at the current time point; The operation data includes the load rate, the ambient temperature, and the operating duration. Specifically: S1: Extract the load rate, the ambient temperature, and the operating duration of the transformer at the current time point. Pre-establish the score conversion rules corresponding to the load rate, the ambient temperature, and the operating duration respectively, and convert the load rate, the ambient temperature, and the operating duration of the transformer at the current time point into a load score, a temperature score, and an operation score respectively. S1-1: Preset the value ranges of each group of load rates corresponding to the load rate. Each value range of the load rate corresponds to a load score; The load score range is set from 1 to 10 and is a positive integer. The higher the load rate of the transformer, the higher the corresponding load score obtained. Preset the value ranges of each group of temperature values corresponding to the ambient temperature. Each value range of the temperature corresponds to a temperature score; The temperature score range is set from 1 to 10 and is a positive integer. The higher the ambient temperature of the transformer, the higher the corresponding temperature score obtained. Preset the value ranges of each group of operating durations corresponding to the operating duration. Each value range of the operating duration corresponds to an operation score; The operation score range is set from 1 to 10 and is a positive integer. The higher the operating duration of the transformer, the higher the corresponding operation score obtained. Taking the load rate as an example, The corresponding relationship between the value range and the score: 0-20% load rate: The corresponding load score is 1; 20-40% load rate: The load score is 3; 40-60% load rate: The load score is 5; 60-80% load rate: The load score is 7; 80-100% load rate: The load score is 10; S2: Mark the load score, the temperature score, and the operation score of the transformer at the current time point as ; At the same time, extract the historical operation data of the transformer within a set time window before the current time point, and also use the score conversion rules to convert the load rate, the ambient temperature, and the operating duration in each group of historical operation data into a load score, a temperature score, and an operation score respectively. After conversion, mark the load score, the temperature score, and the operation score of each group of historical operation data as ; S3: According to the formula perform weighted calculations on the operating data of the transformer at the current time point and the historical operating data of each group to determine the similarity index between the operating data of the transformer at the current time point and the historical operating data of each group ; where are the preset weight coefficients corresponding to the load score, temperature score, and operation score respectively, and the values are set to 1.138, 1.094, and 1.073 respectively; S4: Based on the similarity index between the operating data of the transformer at the current time point and the historical operating data of each group select the historical operating data with the lowest similarity index as the similar historical data of the transformer at the current time point, and use the initial temperature distribution of the similar historical data as the initial temperature distribution of the transformer at the current time point; It should be noted that by comparing the current operating data with the historical data, calculating the similarity index through weighted calculation, and selecting the initial temperature distribution of the similar historical data, it can better fit the actual initial operating state of the transformer. Compared with simply assuming the initial temperature, it greatly improves the accuracy of determining the initial temperature distribution; this is crucial for the reliability of subsequent hot spot temperature detection based on the temperature field distribution calculation, can reduce the calculation deviation caused by inaccurate initial conditions, and more accurately evaluate the operating state of the transformer.

[0020] For example, assume that the current time point is 10:00 on July 15, 2022, and it is necessary to determine the initial temperature distribution of a certain transformer at this time; After monitoring, the current load rate of the transformer is 65%. According to the score conversion rule, in the load rate interval of 60 - 80%, the corresponding load score is 7; The ambient temperature is 32°C, in the ambient temperature interval of 30 - 40°C, the temperature score is 7; The operating duration is 9h, in the operating duration interval of 7 - 10h, the operation score is 7; Set the time window to the past year; extract the historical operating data during this period from the operation and maintenance management system, monitoring device logs, and past maintenance reports; for example, one set of historical data shows that at 14:00 on August 20, 2024, the load rate is 62% (load score is 7), the ambient temperature is 30°C (temperature score is 6), and the operating duration is 8h (operation score is 7); Process all historical operating data according to the score conversion rule to obtain the load score, temperature score, and operation score corresponding to each group of data; Perform calculations similar to the similarity index for all historical operating data groups; after calculation, it is found that the similarity index of the above - mentioned set of historical operating data is the lowest among all historical data groups; Then, take the initial temperature distribution corresponding to this set of similar historical data as the initial temperature distribution of this transformer at 10:00 on July 15, 2022, for subsequent related analyses such as calculating hot spot temperature detection based on the transformer temperature field distribution; Evaluation and correction: Based on the initial temperature distribution of the transformer at the current time point, divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area, and conduct comprehensive evaluations separately. According to the results of the comprehensive evaluation, make a secondary adjustment to the initial temperature distribution of the transformer, and use the adjusted distribution as the final temperature distribution of the transformer corresponding to the temperature field; Specifically: Cooling medium area: Obtain the cooling oil flow rate and cooling oil temperature data of the transformer within a set time window after the current time point, and set the flow rate reference value and temperature reference value of the cooling oil during normal operation of the transformer; For the cooling oil flow rate and cooling oil temperature within the set time window, calculate the average value respectively as the flow rate evaluation value and the temperature evaluation value, denoted as and ; According to the formula weighted calculation is performed on the flow rate evaluation value and the temperature evaluation value of the transformer within the set time window after the current time point to obtain the cooling oil evaluation index of the transformer within the set time window after the current time point; where represent the flow rate reference value and the temperature reference value respectively; are the preset weight coefficients corresponding to the flow rate evaluation value and the temperature evaluation value respectively, and the values are 1.082 and 1.079 respectively; Compare the calculated cooling oil evaluation index with the corresponding preset cooling oil threshold index. If it is higher than the corresponding preset cooling oil threshold index, then calculate the difference between the two and record it as the adjustment difference; Preset the interval where each group of differences corresponding to the adjustment difference is located. Each group of adjustment differences corresponds to a temperature increase set. The temperature increase set includes the temperature increase values of each divided area of the transformer. Based on the calculated adjustment difference, on the basis of the initial temperature distribution, adjust the temperature of each divided area of the transformer by the corresponding temperature increase value; Overall increase the temperature of each part of the transformer. The increase amplitude is determined according to the heat exchange intensity between different parts and the cooling medium. For example, the parts with close heat exchange between the winding and the cooling oil have a larger increase amplitude, up to 6 - 8 °C, while the parts far from the cooling oil circulation path have a smaller increase amplitude, about 4 - 6 °C; It should be noted that when the cooling oil flow rate decreases by 20%, according to the principles of heat transfer, the ability of the cooling oil to carry away heat decreases, and it is estimated that the overall temperature of the transformer will increase by 5 - 8°C. Therefore, based on the initial temperature distribution, the temperatures of all parts of the transformer are increased as a whole, and the increase amplitude is determined according to the heat exchange intensity between different parts and the cooling medium; Winding area: Obtain the winding resistance of the transformer within a set time window after the current time point, and the reference resistance value corresponding to the preset winding resistance; that is, the winding resistance when newly put into operation; Extract the winding resistances at each time point within the set time window as the numerator, and the reference resistance value as the denominator, and calculate the ratio respectively to obtain the resistance ratios at each time point within the set time window; After removing one highest resistance ratio and one lowest resistance ratio, calculate the average value of the remaining groups of resistance ratios to obtain the resistance evaluation ratio of the transformer within the set time window after the current time point; Compare the resistance evaluation ratio within the set time window with the preset resistance threshold ratio. If it is higher than the corresponding preset resistance threshold ratio, calculate the difference between the two and record it as the winding difference; Preset the intervals where each group of differences corresponding to the winding difference is located. Each winding difference corresponds to a winding temperature increase value. After adjusting the temperatures of each partition of the transformer by the corresponding temperature increase values, adjust the adjusted winding area by the corresponding winding temperature increase values; It should be noted that if the winding ages and the resistance increases, according to Joule's law, under the same load current, the generated heat will increase. Assume that through calculation, due to a 5% increase in the winding resistance, the heat generated by the winding increases by 8%. Accordingly, in the initial temperature distribution, the temperature of the winding part needs to be appropriately increased, for example, increased by 3 - 5°C, and the specific value can be determined according to the overall thermal balance of the transformer.

[0021] Core area: Obtain the core permeability of the transformer within a set time window after the current time point, and the reference permeability value corresponding to the preset core permeability; determined based on the standard characteristics of the core material and the design specifications of the transformer; Calculate the average value of the core permeabilities within the set time window and record it as the average permeability rate. Then, starting from the current set time window, extract the average permeability rates of the X time windows before the starting point; where X > 3, and the specific value is set by the technical personnel; Calculate the average magnetic conductance rate for X time windows, denoted as the historical average rate; compare the historical average rate with the magnetic conductance rate of the currently set time window. If the magnetic conductance rate of the currently set time window is less than the historical average rate, it indicates that the magnetic permeability of the transformer core is in a downward trend during this period; then, use the magnetic conductance rate of the currently set time window as the denominator and the historical average rate as the numerator to calculate the ratio, obtaining the magnetic conductance trend ratio of the transformer within the currently set time window, denoted as F. Calculate the magnetic conductance evaluation rate W through the formula W = K - K×(F - 1); where K represents the magnetic conductance rate of the currently set time window; and compare it with the reference magnetic permeability value. If the magnetic conductance rate of the currently set time window is greater than the historical average rate, directly compare the magnetic conductance rate of the currently set time window with the reference magnetic permeability value. If the magnetic conductance evaluation rate is lower than the reference magnetic permeability value, record the difference between the two as the core difference. Preset the intervals where each group of differences corresponding to the preset core differences are located. Each core difference corresponds to an increased value of the core temperature. After adjusting the temperature of each partition of the transformer by the corresponding temperature increase value, adjust the core area after adjustment by the corresponding increased value of the core temperature. It should be noted that by analyzing the change in the magnetic permeability of the core silicon steel sheet, a decrease in magnetic permeability will lead to an increase in core loss and thus generate more heat.

[0022] In the above process of secondary adjustment, the prior art may only consider the temperature field distribution alone to calculate the hot spot temperature, while this method divides the transformer temperature field into the winding area, the core area, and the cooling medium area for comprehensive evaluation respectively. During the evaluation process, not only the flow rate and temperature of the cooling medium and the change in winding resistance are considered, but also multiple factors such as the change in the magnetic permeability of the core are considered, which can more comprehensively reflect the actual operating state of the transformer, thereby more accurately determining the temperature change of each area and making the temperature adjustment more in line with the actual situation. According to the heat exchange intensity between different areas and the cooling medium and the special conditions of each area (such as winding aging, change in core magnetic permeability, etc.), conduct targeted temperature adjustment for each partition of the transformer. For example, the part with close heat exchange between the winding and the cooling oil has a larger increase amplitude, and the part far from the cooling oil circulation path has a smaller increase amplitude. And corresponding temperature increase values are set respectively for the increase in winding resistance and the change in core magnetic permeability, etc., making the adjustment of the temperature distribution more precise, being able to better reflect the actual heat generation situation of each part of the transformer, helping to more accurately detect the hot spot temperature, and improving the safety and reliability of the transformer operation. Real-time update: According to the preset adjustment time interval, after reaching the preset adjustment time interval, re-determine the initial temperature distribution and the final temperature distribution. Verification optimization: Apply the final temperature distribution to a pre-built transformer temperature field calculation model and compare it with the temperature measurement data during the actual operation of the transformer; for example, through devices such as thermocouples and fiber optic sensors installed at key parts of the transformer, the hot spot temperature of the winding, the top oil temperature, the core temperature, etc. are measured in real time. Compare the calculated temperature value with the measured value and calculate the error; if the comparison result shows that the difference between the calculated temperature and the measured temperature in a certain partition area is higher than the corresponding preset allowable value, trigger a deviation signal and send it to the technician; The technician evaluates the reasons for the deviation and makes adjustments. For example, it may be that the aging and the evaluation of the heat dissipation system performance are inaccurate, or the optimization adjustment range is unreasonable, etc. According to the analysis results, re-evaluate the degree of transformer aging and the performance of the heat dissipation system, adjust the optimization adjustment direction and range, and perform secondary optimization adjustment again until the error between the calculated temperature and the measured temperature is within an acceptable range, ensuring that the adjusted initial temperature distribution can more accurately reflect the actual initial operating state of the transformer; The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor limit the invention to the specific embodiments only. Obviously, according to the content of this specification, many modifications and changes can be made. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A hot spot temperature detection method based on the calculation of the transformer temperature field distribution, characterized in that, Including: Determine the initial conditions: Extract the historical operation data of the transformer within a set time window before the current time point; And conduct a comprehensive evaluation with the operation data of the transformer at the current time point to determine the initial temperature distribution of the transformer at the current time point; Wherein the operation data includes the load rate, ambient temperature, and the operating duration; Evaluation and correction: Based on the initial temperature distribution of the transformer at the current time point, divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct a comprehensive evaluation for each area respectively. According to the results of the comprehensive evaluation, make a secondary adjustment to the initial temperature distribution of the transformer, and use the adjusted result as the final temperature distribution of the corresponding temperature field of the transformer.

2. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 1, wherein Extract the historical operation data of the transformer within a set time window before the current time point; and conduct a comprehensive evaluation with the operation data of the transformer at the current time point. Specifically: Extract the load rate, ambient temperature, and operating duration of the transformer at the current time point, pre-establish the score conversion rules corresponding to the load rate, ambient temperature, and operating duration respectively, and convert the load rate, ambient temperature, and operating duration of the transformer at the current time point into a load score, a temperature score, and an operation score respectively; Mark the load score, temperature score, and operation score of the transformer at the current time point as ; at the same time, extract the historical operation data of the transformer within the set time window before the current time point, and also use the score conversion rules to convert the load rate, ambient temperature, and operating duration in each group of historical operation data into load score, temperature score, and operation score respectively. After conversion, mark the load score, temperature score, and operation score of each group of historical operation data as .

3. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 2, characterized in that, Determine the initial temperature distribution of the transformer at the current time point. Specifically: According to the formula Perform weighted calculations on the operating data of the transformer at the current time point and the historical operating data of each group to determine the similarity index between the operating data of the transformer at the current time point and the historical operating data of each group ; where Are respectively the preset weight coefficients corresponding to the load score, temperature score, and operation score; Based on the similarity index between the operating data of the transformer at the current time point and the historical operating data of each group , select the similarity index The lowest historical operating data is used as the similar historical data of the transformer at the current time point, and the initial temperature distribution of the similar historical data is used as the initial temperature distribution of the transformer at the current time point.

4. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 3, characterized in that Pre-establish the score conversion rules corresponding to the load rate, ambient temperature, and operating duration respectively. Specifically: Preset the value range of each group of load rates corresponding to the load rate, and each value range of load rates corresponds to a load score; preset the value range of each group of temperatures corresponding to the ambient temperature, and each value range of temperatures corresponds to a temperature score; Preset the value range of each group of operating durations corresponding to the operating duration, and each value range of operating durations corresponds to an operation score.

5. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 4, characterized in that, Divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct a comprehensive evaluation for each area respectively. The specific process of evaluating the cooling medium area is: Obtain the cooling oil flow rate and cooling oil temperature data of the transformer within a set time window after the current time point, and set the flow reference value and temperature reference value of the cooling oil during normal operation of the transformer; For the cooling oil flow rate and cooling oil temperature within the set time window, the average values are calculated respectively as the flow rate evaluation value and the temperature evaluation value, denoted as and ; According to the formula evaluate the flow rate of the transformer within the set time window after the current time point and the temperature evaluation value perform weighted calculation to obtain the cooling oil evaluation index of the transformer within the set time window after the current time point ; where respectively represent the flow rate reference value and the temperature reference value; are the preset weight coefficients corresponding to the flow rate evaluation value and the temperature evaluation value respectively. Compare the calculated cooling oil evaluation index with the corresponding preset cooling oil threshold index. If it is higher than the corresponding preset cooling oil threshold index, then record the difference between the two as the adjustment difference; Preset the interval of each group of differences corresponding to the adjustment difference, and each adjustment difference corresponds to a temperature increase set, and the temperature increase set includes the temperature increase values of each divided area of the transformer.

6. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 5, characterized in that, Divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct a comprehensive evaluation for each area respectively. The specific process of evaluating the winding area is: Obtain the winding resistance of the transformer within a set time window after the current time point, and preset the reference resistance value corresponding to the winding resistance; extract the winding resistance at each time point within the set time window as the numerator, and the reference resistance value as the denominator, and calculate the ratio respectively to obtain the resistance ratio at each time point within the set time window; After removing the highest resistance ratio and the lowest resistance ratio, calculate the average value of the remaining groups of resistance ratios to obtain the resistance evaluation ratio of the transformer within a set time window after the current time point; Compare the resistance evaluation ratio within the set time window with the preset resistance threshold ratio. If it is higher than the corresponding preset resistance threshold ratio, calculate the difference between the two and record it as the winding difference; The intervals where the difference values corresponding to the preset winding differences are located, and each winding difference corresponds to an increase value of the winding temperature.

7. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 6, characterized in that, Divide the transformer temperature field into a winding area, an iron core area, and a cooling medium area and conduct comprehensive evaluations respectively. The specific process for evaluating the iron core area is as follows: Obtain the magnetic permeability of the iron core of the transformer within a set time window after the current time point, and the reference magnetic permeability value corresponding to the preset magnetic permeability of the iron core; Calculate the average value of the magnetic permeability of the iron core within the set time window, denoted as the average magnetic permeability rate, and then starting from the current set time window, extract the average magnetic permeability rates of the X time windows before the starting point; where X > 3; Calculate the average value of the average magnetic permeability rates of the X time windows, denoted as the historical average rate; compare the historical average rate with the average magnetic permeability rate of the current set time window. If the average magnetic permeability rate of the current set time window is less than the historical average rate, then use the average magnetic permeability rate of the current set time window as the denominator and the historical average rate as the numerator to calculate the ratio, and obtain the magnetic permeability trend ratio of the transformer within the current set time window, denoted as F; Calculate the magnetic permeability evaluation rate W through the formula W = K - K×(F - 1); where K represents the average magnetic permeability rate of the current set time window; and compare it with the reference magnetic permeability value. If the magnetic permeability evaluation rate is lower than the reference magnetic permeability value, then calculate the difference between the two and denote it as the iron core difference; The intervals where the difference values corresponding to the preset iron core differences are located, and each iron core difference corresponds to an increase value of the iron core temperature.

8. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 7, characterized in that, Based on the results of the comprehensive evaluation, make a secondary adjustment to the initial temperature distribution of the transformer, specifically: Based on the calculated adjustment difference, on the basis of the initial temperature distribution, adjust the temperature of each divided area of the transformer by the corresponding temperature increase value; after adjusting the temperature of each divided area of the transformer by the corresponding temperature increase value, adjust the adjusted winding area by the corresponding winding temperature increase value; after adjusting the temperature of each divided area of the transformer by the corresponding temperature increase value, adjust the adjusted iron core area by the corresponding iron core temperature increase value; after the adjustment is completed, it is used as the final temperature distribution of the corresponding temperature field of the transformer.

9. The hot spot temperature detection method based on the calculation of the transformer temperature field distribution according to claim 8, characterized in that, It also includes: Real-time update: According to the preset adjustment time interval, after reaching the preset adjustment time interval, re-determine the initial temperature distribution and the final temperature distribution; Verification and optimization: Apply the final temperature distribution to the pre-constructed transformer temperature field calculation model and compare it with the temperature measurement data during the actual operation of the transformer; if the comparison result shows that the difference between the calculated temperature and the measured temperature in a certain divided area is higher than the corresponding preset allowable value, then trigger a deviation signal and send it to the technician.

Images