A two-stage short-time small current-based dry-type transformer capacity rapid evaluation method and system

Abstract

The application belongs to the field of electrical engineering, and relates to a two-stage short-time small-current-based dry-type transformer capacity rapid evaluation method and system, which comprises the following steps: inputting a first-stage small current I1 to the winding of a transformer, collecting winding temperature data T(t)1 of the first stage until a steady state is reached; directly increasing the current to a second-stage small current I2 without interrupting the power supply, and continuing to collect winding temperature data T(t)2 of the second stage until a steady state is reached again; fitting the winding temperature data T(t)1 and T(t)2, outputting an exponential model and exponential model parameters; inputting the exponential model parameters into a power function model related to a load rate, and outputting power function model parameters; setting the load rate to 100%, and calculating the temperature rise steady value and time constant under the 100% transformer rated current I e Based on the GB / T1094.12 standard, the winding average temperature rise is compared with the maximum allowable temperature rise value, and the actual capacity and carrying capacity of the transformer are evaluated. The application has the effects of energy saving and consumption reduction and efficiency improvement.

Description

Technical Field

[0001] This application belongs to the field of electrical engineering, and in particular relates to a method and system for rapid capacity assessment of dry-type transformers based on two-stage short-time low current. Background Technology

[0002] Temperature rise testing is an important type of test for evaluating the temperature rise performance of dry-type transformers under rated load, playing a crucial role in ensuring the safe operation and reliability of transformers. According to GB / T 1094.11-2022 "Power Transformers Part 11: Dry-type Transformers" standard, temperature rise testing mainly involves measuring the temperature rise of the transformer windings under rated current. Commonly used temperature rise testing methods include the simulated load method, the mutual load method, and the direct load method. Among these, the simulated load method is the preferred choice for on-site testing because it does not require an additional transformer or load equipment.

[0003] According to GB / T 1094.11-2022 "Power Transformers - Part 11: Dry-type Transformers", the stable current at 100% of the rated current should be less than 1 kA, while the stable current at 40% and 60% of the rated current should be less than 0.4 kA and 0.6 kA, respectively. According to IEC 60076-11 "Power Transformers - Part 11: Dry-type Transformers", the stable current at 100% of the rated current should be less than 1.25 kA, while the stable current at 40% and 60% of the rated current should be less than 0.5 kA and 0.75 kA, respectively.

[0004] However, the simulated load method faces some challenges in practical applications, particularly in terms of power supply capacity limitations and test time.

[0005] Limitations of existing technologies:

[0006] Power supply capacity limitation: During field load temperature rise tests, insufficient power supply capacity is often a problem, especially in remote areas or small substations, making it difficult to meet the high current requirements of the test. According to GB / T1094.11-2022, when the input test current is lower than the rated current I... N But not less than 90% N At that time, after the core and winding temperatures have both stabilized, apply I N The winding temperature rise Δθ was measured by resistance method. t And correct it to the temperature rise Δθ under rated load according to the given formula. N In short, the standard test current must not be lower than 90% of the rated current. When the input test current is lower than the rated current I... N But not less than 90% N At that time, although the winding temperature rise Δθ can be measured by the resistance method, t And corrected to the temperature rise Δθ under rated load. NHowever, the on-site power supply capacity often cannot meet this requirement, which leads to the failure of the test or the deviation of the results.

[0007] Long test duration: Temperature rise tests may last for tens of hours, which not only prolongs the power outage time and affects the stability of the power system, but may also cause unnecessary damage to the transformer.

[0008] To improve the accuracy of temperature rise tests, a method and device for predicting rapid temperature rise in transformers by mapping small current to large current (CN 117849494B) proposes a three-stage extrapolation calculation model. This method acquires temperature rise datasets of the transformer under different load rates, including the first steady-state temperature rise value, the heating rate, and the second steady-state temperature rise value. Then, it uses a pre-defined mathematical function model fitting strategy to determine the temperature rise data changes of the transformer under different load rates. The method also includes verifying the temperature rise data to correct for variations, thereby improving the accuracy of the prediction. Although the three-stage method has advantages in accuracy, its operation is relatively complex and time-consuming.

[0009] Therefore, improvements are needed. Summary of the Invention

[0010] To achieve energy conservation, consumption reduction, and efficiency improvement, this application provides a method and system for rapid capacity assessment of dry-type transformers based on two-stage short-time low current.

[0011] The first objective of this invention is achieved through the following technical solution:

[0012] A rapid capacity assessment method for dry-type transformers based on two-stage short-time low-current operation includes the following steps:

[0013] A small initial current I1 is input to the transformer windings. This small initial current I1 is equal to the transformer's rated current I. e 40%, and collect the winding temperature data T(t)1 of the first section until a steady state is reached;

[0014] Without interrupting the power supply, the current is directly increased to the second small current I2, which is the transformer's rated current I. e 60%, and continue to collect the winding temperature data T(t)2 of the second section until it reaches a steady state again;

[0015] The winding temperature data T(t)1 and T(t)2 are fitted using the least squares method, and the exponential model and exponential model parameters are output.

[0016] Input the parameters of the exponential model into the power function model related to the load factor, and output the parameters of the power function model.

[0017] The load rate is set to 100%, and the temperature rise steady value and time constant under 100% transformer rated current I e are calculated based on the power function model and power function model parameters.

[0018] Based on the GB / T1094.12 standard, the average winding temperature rise and the maximum allowable temperature rise value are output, and the winding average temperature rise and the maximum allowable temperature rise value are compared to evaluate the actual capacity and carrying capacity of the transformer.

[0019] In a preferred embodiment, the step of directly increasing the current to the second small current I2 without interrupting the power supply, the second small current I2 is 60% of the transformer rated current I e , and the winding temperature data T(t)2 of the second section is continuously collected until the steady state is reached again, including the steps of:

[0020] Directly adjusting the current of the transformer winding from I1 to I2 without interrupting the power supply, I1=0.4·I e , I2=0.6·I e , and collecting the winding temperature data T(t)2 of the second section;

[0021] Calculate the temperature difference ΔT2 between the i-th winding temperature data and the i-1-th winding temperature data and the corresponding time difference Δt2;

[0022] Based on the preset formula , the average temperature change rate V2 is output;

[0023] When the average temperature change rate V2 of the continuous 10 winding temperature data is less than the preset threshold ε, it is judged that the winding temperature data T(t)2 reaches the steady state, and the second section temperature rise steady value T(t) b is output.

[0024] In a preferred embodiment, the step of fitting the winding temperature data T(t)1, T(t)2 based on the least squares method and outputting the exponential model and exponential model parameters includes the steps of:

[0025] For a load rate of 40%, the first section winding temperature data T(t)1 collected is fitted based on the least squares formula , and the exponential model Y1=a 40％ (1-exp(-t / b 40％ )), the temperature rise steady value a 40％ , and the time constant b 40％ are output.

[0026] For a load rate of 60%, the first section winding temperature data T(t)1 collected is fitted based on a 60％ =T(t) b , m = Vp c p , pre-measured Vp c p , deduce output time constant b 60％ .

[0027] In a preferred embodiment, the step of inputting the exponential model parameters into the power function model related to the load rate, and outputting the power function model parameters, comprises the steps of:

[0028] SA1: when the load rate is 40%, input N = 40%, x = 0.4 into the power function model a N = nx m , b N = px r ;

[0029] SA2: when the load rate is 60%, input N = 60%, x = 0.6 into the power function model a N = nx m , b N = px r ;

[0030] SA3: based on SA1-SA2, output the model parameters n, m, p, r.

[0031] In a preferred embodiment, the step of setting the load rate to 100%, and calculating the temperature rise stability value and time constant under 100% transformer rated current I e based on the power function model and the power function model parameters, comprises the steps of:

[0032] when the load rate is 100%, input N = 100%, x = 1, n, m, p, r into the power function model a N = nx m , b N = px r , and calculate the temperature rise stability value a 100％ and the time constant b 100％ .

[0033] In a preferred embodiment, the step of outputting the winding average temperature rise and the maximum allowable temperature rise value based on the GB / T1094.12 standard, and comparing the winding average temperature rise with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer, comprises the steps of:

[0034] output the winding average temperature rise T based on the GB / T1094.12 standard max ;

[0035] based on a 100％ , calculate the winding average temperature rise Tavg , and compared with the maximum allowed temperature rise value T max ;

[0036] When T avg ≤ T max , it is considered that the transformer can withstand the rated capacity of the transformer, and the actual capacity and carrying capacity meet the requirements;

[0037] When T avg > T max , it is considered that the transformer cannot withstand the rated capacity of the transformer, and the use capacity needs to be reduced.

[0038] The above-mentioned purpose two of the present application is realized by the following technical scheme:

[0039] A two-stage short-time small current-based dry-type transformer capacity rapid evaluation system, comprising:

[0040] The first module: inputting a first-stage small current I1 to the winding of the transformer, the first-stage small current I1 being 40% of the rated current I e of the transformer, and collecting winding temperature data T(t)1 of the first stage until reaching a steady state;

[0041] The second module: directly increasing the current to a second-stage small current I2 without interrupting the power supply, the second-stage small current I2 being 60% of the rated current I e of the transformer, and continuing to collect winding temperature data T(t)2 of the second stage until reaching a steady state again;

[0042] The third module: fitting the winding temperature data T(t)1 and T(t)2 based on the least square method, and outputting an exponential model and exponential model parameters;

[0043] The fourth module: inputting the exponential model parameters into a power function model related to the load rate, and outputting power function model parameters;

[0044] The fifth module: setting the load rate to 100%, and based on the power function model and the power function model parameters, calculating the temperature rise steady value and the time constant under the rated current I e of 100% of the transformer;

[0045] The sixth module: based on the GB / T1094.12 standard, outputting the winding average temperature rise, and comparing with the maximum allowed temperature rise value to evaluate the actual capacity and carrying capacity of the transformer.

[0046] The above-mentioned purpose three of the present application is realized by the following technical scheme:

[0047] The computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the two-stage short-time small current-based dry-type transformer capacity rapid evaluation method when executing the computer program.

[0048] The fourth purpose of the application is achieved by the following technical solution:

[0049] A computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the steps of the two-stage short-time small current-based dry-type transformer capacity rapid evaluation method.

[0050] In summary, the application has at least one of the following beneficial technical effects:

[0051] An innovative test method is implemented, which sequentially inputs short-time small currents I1, I2 and the rated current I of the transformer to the transformer winding e , and continuously monitors the temperature change of the winding until the system reaches a steady state. This process can obtain the temperature rise steady value and time constant under different load rates of 40% and 60%. In order to accurately analyze these data, the least squares method is used to fit the winding temperature data, thereby outputting the exponential model parameters. These parameters are then input into a power function model related to the load rate to calculate the temperature rise steady value and time constant under the rated current of the transformer. In addition, the technical solution adopts a unique two-stage continuous short-time small current temperature rise test method, which is specially designed to obtain the temperature rise data of the dry-type transformer winding under the rated current. This test method replaces the traditional short-circuit temperature rise test which takes 15 to 20 hours, greatly improving the efficiency of the test. Specifically, through this two-stage test, 6 to 10 hours of test time can be saved, and more than half of the electricity cost can be saved, which not only improves the economy of the test, but also reduces energy consumption. Finally, the average winding temperature rise is evaluated based on the GB / T1094.12 standard, and compared with the maximum allowable temperature rise value, so as to accurately evaluate the actual capacity and carrying capacity of the transformer, and ensure its safe and reliable operation. This method not only improves the efficiency and accuracy of the test, but also significantly improves the practicability and economy of the entire evaluation process by using an efficient test method. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 is the implementation flowchart of the two-stage short-time small current-based dry-type transformer capacity rapid evaluation method of the application;

[0053] Figure 2The dynamic temperature rise curve of the transformer winding hot spot under different load rates (40%, 60%) is shown in the following figure:

[0054] Figure 3 The two-stage continuous short-time small current temperature rise test principle diagram is shown in the following figure:

[0055] Figure 4 The implementation flowchart of step S40 in the embodiment of the dry-type transformer capacity rapid evaluation method based on two-stage short-time small current is shown in the following figure:

[0056] Figure 5 The implementation flowchart of step S50 in the embodiment of the dry-type transformer capacity rapid evaluation method based on two-stage short-time small current is shown in the following figure:

[0057] Figure 6 The implementation flowchart of step S60 in the embodiment of the dry-type transformer capacity rapid evaluation method based on two-stage short-time small current is shown in the following figure:

[0058] Figure 7 The principle block diagram of the computer device is shown in the following figure. DETAILED DESCRIPTION

[0059] The following will be described in detail with reference to the accompanying drawings. Figures 1-7 The present application will be further described in detail.

[0060] In an embodiment, as shown in the following figure, the present application discloses a dry-type transformer capacity rapid evaluation method based on two-stage short-time small current, which specifically includes the following steps: Figure 1

[0061] S10: input a first-stage small current I1 to the winding of the transformer, the first-stage small current I1 is 40% of the rated current I of the transformer, and collect the winding temperature data T(t)1 of the first stage until reaching the steady state; e

[0062] S20: directly increase the current to a second-stage small current I2 without interrupting the power supply, the second-stage small current I2 is 60% of the rated current I of the transformer, and continue to collect the winding temperature data T(t)2 of the second stage until reaching the steady state again; e

[0063] S30: fit the winding temperature data T(t)1, T(t)2 based on the least square method, output the exponential model and the exponential model parameters;

[0064] S40: input the exponential model parameters into the power function model related to the load rate, and output the power function model parameters;

[0065] ​​​S50: Set the load ratio to 100%, calculate the temperature rise steady value and time constant under 100% transformer rated current I based on the power function model and power function model parameters. e

[0066] S60: Based on GB / T1094.12 standard, output the winding average temperature rise and the maximum allowable temperature rise value, and compare the winding average temperature rise with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer.

[0067] In this embodiment, an innovative test method is implemented, which sequentially inputs short-time small currents I1, I2 and transformer rated current I to the transformer winding e , while continuously monitoring the temperature change of the winding until the system reaches steady state. This process can obtain the temperature rise steady value and time constant under different load ratios of 40% and 60%. In order to accurately analyze these data, the least squares method is used to fit the winding temperature data, thereby outputting the exponential model parameters. These parameters are then input into a power function model related to the load ratio to calculate the temperature rise steady value and time constant under the transformer rated current.

[0068] In addition, the present technical solution adopts a unique two-stage continuous short-time small current temperature rise test method, which is specially designed to obtain the temperature rise data of the dry-type transformer winding under the rated current. This test method replaces the traditional short-circuit temperature rise test which takes 15 to 20 hours, greatly improving the efficiency of the test. Specifically, through this two-stage test, 6 to 10 hours of test time can be saved, and more than half of the electricity cost can be saved, which not only improves the economy of the test, but also reduces energy consumption.

[0069] Finally, based on the GB / T1094.12 standard, the winding average temperature rise is evaluated and compared with the maximum allowable temperature rise value, so as to accurately evaluate the actual capacity and carrying capacity of the transformer, and ensure its safe and reliable operation. This method not only improves the efficiency of the test and the accuracy of the results, but also significantly improves the practicality and economy of the entire evaluation process by using an efficient test method.

[0070] As Figure 2 , S20 step, comprising the steps of:

[0071] S201: Without interrupting the power supply, directly adjust the current of the transformer winding from I1 to I2, I1 = 0.4·I e , I2 = 0.6·I e , and collect the winding temperature data T(t)2 of the second stage;

[0072] ​S202: Calculate the temperature difference ΔT2 between the i-th winding temperature data and the i-1-th winding temperature data and the corresponding time difference Δt2;

[0073] S203: Based on the preset formula output the average temperature change rate V2;

[0074] S204: When the average temperature change rate V2 of the continuous 10 winding temperature data is less than the preset threshold ε, it is judged that the winding temperature data T(t)2 reaches steady state, and the second segment temperature rise stable value T(t) b .

[0075] In this embodiment, S20 step is to directly adjust 40% transformer rated current I e to 60% transformer rated current I e without interrupting the power supply, continue to apply the current I2 to the transformer winding, and collect temperature data in real time based on high-precision thermocouple. Then, the temperature difference ΔT2 and the time difference Δt2 between adjacent temperature data points are calculated, and the average temperature change rate V2 is output based on the preset formula When the average temperature change rate V2 of the continuous 10 winding temperature data is less than the preset threshold ε, it is judged that the winding temperature T(t)2 has reached steady state, and the second segment temperature rise stable value T(t) b . This method ensures smooth transition of load rate, avoids temperature fluctuation caused by power-off and restart, provides continuous and accurate temperature data, and provides reliable basis for evaluating the temperature rise characteristics of transformer under higher load conditions.

[0076] As Figure 3 , S30 step, including steps:

[0077] S301: For load rate 40%, based on the least square method formula fit the collected first segment winding temperature data T(t)1, output the exponential model Y1=a 40％ (1-exp(-t / b 40％ )), temperature rise stable value a 40％ , time constant b 40％ ;

[0078] S302: For load rate 60%, based on a 60％ =T(t) b , m=Vρc p , pre-measured Vρc p , deduce output time constant b 60％ .

[0079] In this embodiment, the step S30 fits the temperature time series under the load of 40% by the least square method, and outputs the exponential model Y1=a 40％ (1-exp(-t / b 40％ )) and the temperature rise stable value a 40％ , the time constant b 40％ . Based on a 60％ , m=Vρc p , the pre-measured Vρc p , the time constant b 60％ under the load of 60% is determined.

[0080] As Figure 4 , the step S40 includes steps:

[0081] SA1: when the load rate is 40%, input N=40%, x=0.4 into the power function model a N =nx m , b N =px r ;

[0082] SA2: when the load rate is 60%, input N=60%, x=0.6 into the power function model a N =nx m , b N =px r ;

[0083] SA3: based on SA1-SA2, output the model parameters n, m, p, r.

[0084] In this embodiment, the thermal response characteristics of the transformer are fitted by inputting the corresponding temperature rise stable values into the power function model under two different load rates of 40% and 60%. The steps SA1 and SA2 process the data input under different load rates, and the step SA3 calculates the parameters of the power function model based on the input. The effect of this method is that it can effectively quantify the thermal time constant and temperature rise rate of the transformer, so as to realize the rapid and accurate evaluation of the capacity of the transformer. In this way, not only the scientificity and systematicness of the evaluation process are improved, but also the accuracy and practicality of the evaluation results are ensured, which helps to ensure the stable operation of the transformer and prolong its service life.

[0085] As Figure 5 , the step S50 includes steps:

[0086] S501: when the load rate is 100%, input N=100%, x=1, n, m, p, r into the power function model a N =nx m , b N=px r Calculate the stable temperature rise value a 100％ Time constant b 100％ .

[0087] In this embodiment, a power function model is used to model the thermal characteristics of the transformer. By inputting specific parameters, the temperature rise stability and time constant of the transformer at 100% load are calculated. Step S501 specifically implements this process, which integrates all relevant parameters into the power function model a. N =nx m b N =px r Then, the stable temperature rise value 'a' under 100% load rate was calculated. 100％ and time constant b 100％ The advantage of this method lies in its ability to accurately simulate the thermal behavior of transformers under actual operating conditions, providing crucial data for evaluating their long-term performance. This approach not only rapidly determines the transformer's thermal stability but also improves the accuracy of the assessment results, aiding in the prediction of overheating risks, ensuring safe operation and design optimization, and providing reliable data support for transformer maintenance and fault diagnosis.

[0088] like Figure 6 Step S60 includes the following steps:

[0089] S601: Based on GB / T1094.12 standard, average temperature rise of output winding Maximum permissible temperature rise T max ;

[0090] S602: Based on a 100％ Calculate the average temperature rise T of the winding. avg and the maximum allowable temperature rise T max Compare;

[0091] S603: When T avg ≤T max At that time, it was believed that the transformer could withstand the rated capacity of the transformer, and the actual capacity and load-bearing capacity met the requirements;

[0092] S604: When T avg >T max At that time, it was believed that the transformer could not withstand the rated capacity of the transformer and that the operating capacity needed to be reduced.

[0093] In the embodiment, the core of step S60 is to determine the operation state of the transformer by monitoring and calculating the winding average temperature rise of the transformer, and comparing it with the specified maximum allowable temperature rise value. S601: Based on the national standard GB / T1094.12, output the winding average temperature rise Maximum allowable temperature rise value T max These standard parameters are important basis to ensure that the transformer meets the requirements in safety and performance. S602: Calculate the winding average temperature rise T 100％ using the real-time monitored temperature rise stable value a avg This is done by measuring the temperature change of the transformer under the load rate of 100%. When the condition S603 is met, i.e. the winding average temperature rise T avg is less than or equal to the maximum allowable temperature rise value T max , it can be considered that the transformer can withstand its rated capacity, and the actual capacity and carrying capacity meet the requirements. If the condition S604 is met, i.e. the winding average temperature rise T avg is greater than the maximum allowable temperature rise value T max , it indicates that the transformer cannot withstand its rated capacity, and the use capacity needs to be reduced to prevent overheating. This method thus provides a preventive measure, which helps to prolong the service life of the transformer and ensures the stable operation of the power system.

[0094] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0095] In an embodiment, a two-stage short-time small current-based dry-type transformer capacity rapid evaluation system is provided, which corresponds to the two-stage short-time small current-based dry-type transformer capacity rapid evaluation method described above. The two-stage short-time small current-based dry-type transformer capacity rapid evaluation system comprises:

[0096] First module: input a first-stage small current I1 to the winding of the transformer, the first-stage small current I1 being 40% of the rated current I e of the transformer, and collect the winding temperature data T(t)1 of the first stage until reaching a steady state;

[0097] Second module: directly increase the current to a second-stage small current I2 without interrupting the power supply, the second-stage small current I2 being 60% of the rated current I e of the transformer, and continue to collect the winding temperature data T(t)2 of the second stage until reaching a steady state again;

[0098] The third module: fitting the winding temperature data T(t) 1, T(t) 2 based on the least square method, outputting an exponential model and an exponential model parameter;

[0099] The fourth module: inputting the exponential model parameter into a power function model related to the load rate, and outputting a power function model parameter;

[0100] The fifth module: setting the load rate as 100%, and calculating the temperature rise stable value and the time constant under 100% transformer rated current I based on the power function model and the power function model parameter; e

[0101] The sixth module: outputting the winding average temperature rise based on the GB / T1094.12 standard, and comparing the winding average temperature rise with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer.

[0102] Optionally, the method further comprises:

[0103] The first acquisition module: directly adjusting the current of the transformer winding from I 1 to I 2 without interrupting the power supply, I 1 = 0.4·I e , I 2 = 0.6·I e , and collecting the winding temperature data T(t) 2 of the second section;

[0104] The first calculation module: calculating the temperature difference ΔT 2 between the i th winding temperature data and the i-1 th winding temperature data and the corresponding time difference Δt 2;

[0105] The first output module: outputting the average temperature change rate V 2 based on a preset formula

[0106] The second output module: when the average temperature change rates V 2 of the continuous 10 winding temperature data are all less than a preset threshold ε, judging that the winding temperature data T(t) 2 reaches a steady state, and outputting the second section temperature rise stable value T(t) b .

[0107] Optionally, the method further comprises:

[0108] The third output module: for the load rate of 40%, fitting the collected first section winding temperature data T(t) 1 based on a least square method formula , outputting an exponential model Y 1 = a 40％ (1-exp(-t / b 40％ )), a temperature rise stable value a 40％ , and a time constant b 40％ ;

[0109] The fourth output module: for the load rate of 60%, based on a 60％ = T(t) b ​​、 m = Vp c p , pre-measured Vp c p , deduce output time constant b 60％ .

[0110] Optionally, further comprising:

[0111] The first input module: when the load rate is 40%, input N = 40%, x = 0.4 into the power function model a N = nx m , b N = px r .

[0112] The second input module: when the load rate is 60%, input N = 60%, x = 0.6 into the power function model a N = nx m , b N = px r .

[0113] The fifth output module: based on SA1-SA2, output model parameters n, m, p, r.

[0114] Optionally, further comprising:

[0115] The third calculation module: when the load rate is 100%, input N = 100%, x = 1, n, m, p, r into the power function model a N = nx m , b N = px r , calculate the temperature rise stable value a 100％ , time constant b 100％ .

[0116] Optionally, further comprising:

[0117] The eighth output module: based on GB / T1094.12 standard, output winding average temperature rise Maximum allowable temperature rise value T max ;

[0118] The first module: based on a 100％ , calculate the winding average temperature rise T avg , and compare with the maximum allowable temperature rise value T max ;

[0119] The first judgment module: when T avg ≤ T max , it is considered that the transformer can withstand the rated capacity of the transformer, and the actual capacity and carrying capacity meet the requirements;

[0120] Second judging module: when T avg > T max it is considered that the transformer cannot withstand the rated capacity of the transformer, and the use capacity needs to be reduced.

[0121] For specific limitations of the two-stage short-time small current-based dry-type transformer capacity rapid evaluation system, refer to the limitations of the two-stage short-time small current-based dry-type transformer capacity rapid evaluation method in the foregoing, which will not be repeated here. Each module in the two-stage short-time small current-based dry-type transformer capacity rapid evaluation system can be realized by software, hardware, and combinations thereof, in whole or in part. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each of the above modules.

[0122] In one embodiment, a computer device, which can be a server, is provided, and an internal structure diagram thereof can be as shown in Figure 7 The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is used to store temperature rise stability values and time constants. The network interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to implement a two-stage short-time small current-based dry-type transformer capacity rapid evaluation method.

[0123] In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements a two-stage short-time small current-based dry-type transformer capacity rapid evaluation method when executing the computer program.

[0124] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement a two-stage short-time small current-based dry-type transformer capacity rapid evaluation method.

[0125] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of functional units and modules is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A two-stage short-time small current-based dry-type transformer capacity rapid evaluation method, characterized in that, The method comprises the steps of: A small initial current I1 is input to the transformer windings. This small initial current I1 is equal to the transformer's rated current I. e 40%, and collect the winding temperature data T(t)1 of the first section until a steady state is reached; Without interrupting the power supply, the current is directly raised to a second segment of small current I2, which is 60% of the transformer rated current I e and the second segment winding temperature data T(t)2 is continuously collected until the steady state is reached again; fitting the winding temperature data T(t)1 and T(t)2 based on a least square method, outputting an exponential model and exponential model parameters; inputting the exponential model parameters into a power function model related to the load rate, and outputting power function model parameters; The load rate is set to 100%, and the temperature rise stability value and time constant under 100% transformer rated current I e are calculated based on the power function model and power function model parameters. based on GB / T1094.12 standard, outputting winding average temperature rise and maximum allowable temperature rise value, and comparing the winding average temperature rise with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer.

2. The method for rapid evaluation of the capacity of dry-type transformers based on two-stage short-time small current according to claim 1, characterized in that, said step of directly boosting the current to a second segment of small current I2, said second segment of small current I2 being 60% of the transformer rated current I e and continuing to collect the winding temperature data T(t)2 of the second segment until the steady state is reached again, comprises the steps of: Without interrupting the power supply, the current of the transformer winding is directly adjusted from I1 to I2, I1 = 0.4 I e , I2 = 0.6 I e , and the winding temperature data T(t)2 of the second section is collected; calculating the temperature difference ΔT2 between the i-th winding temperature data and the i-1-th winding temperature data and the corresponding time difference Δt2; based on a preset formula output the average temperature change rate V2; When the average temperature change rate V2 of the 10 consecutive winding temperature data is less than the preset threshold ε, it is determined that the winding temperature data T(t)2 reaches a steady state, and a second section temperature rise steady value T(t) is output b .

3. The method for rapid evaluation of capacity of dry-type transformer based on two-stage short-time small current according to claim 1, characterized in that, The step of fitting the winding temperature data T(t)1 and T(t)2 based on a least square method, outputting an exponential model and exponential model parameters, comprises the steps of: For a load ratio of 40%, based on the least squares formula Fitting the collected winding temperature data T(t)1 of the first section, outputting the exponential model Y1 = a 40％ (1 - exp(-t / b 40％ )), the temperature rise steady value a 40％ , and the time constant b 40％ ; For a load ratio of 60%, based on a 60％ = T(t) b , m = Vpc p , the pre-measured Vpc p , it is deduced that Output time constant b 60％ .

4. The method for rapid evaluation of the capacity of dry-type transformers based on two-stage short-time small current according to claim 1, characterized in that, The step of inputting the exponential model parameters into a power function model related to the load rate, and outputting power function model parameters, comprises the steps of: SA1: When the load rate is 40%, input N=40%, x=0.4 into the power function model SA2: When the load rate is 60%, input N=60%, x=0.6 into the power function model SA3: based on SA1-SA2, outputting model parameters n, m, p, r.

5. The method for rapid evaluation of capacity of dry-type transformer based on two-stage short-time small current according to claim 1, characterized in that, The load rate is set to 100%, and based on the power function model and the power function model parameters, the temperature rise stability value and the time constant under 100% transformer rated current I e The steps of setting the load rate to 100%, and based on the power function model and the power function model parameters, calculating the temperature rise stability value and the time constant under 100% transformer rated current I e The steps of setting the load rate to 100%, and based on the power function model and the power function model parameters, calculating the temperature rise stability value and the When the load rate is 100%, input N=100%, x=1, n, m, p, r into the power function model Calculate the temperature rise stability value a 100％ , time constant b 100％ .

6. The method for rapid evaluation of dry-type transformer capacity based on two-stage short-time small current according to claim 1, characterized in that, The step of based on GB / T1094.12 standard, outputting winding average temperature rise, and comparing with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer, comprises the steps of: Output winding average temperature rise based on GB / T1094.12 standard Maximum allowable temperature rise value T max ; Based on a 100％ , the winding average temperature rise T avg is calculated and compared with the maximum allowable temperature rise value T max ; When T avg ≤ T max , it is considered that the transformer can withstand the transformer rated capacity, actual capacity and carrying capacity meet the requirements; When T avg > T max , it is considered that the transformer cannot withstand the rated capacity of the transformer, and the use capacity needs to be reduced.

7. A two-stage short-time small current-based dry-type transformer capacity rapid evaluation system, characterized in that, It comprises: Module 1: Input a small current I1 into the transformer windings. This small current I1 is the transformer's rated current I. e 40%, and collect the winding temperature data T(t)1 of the first section until a steady state is reached; Second module: the current is directly boosted to a second segment of small current I2, which is 60% of the transformer rated current I e and the second segment winding temperature data T(t)2 is continuously collected until the steady state is reached again; The third module: fitting the winding temperature data T(t)1 and T(t)2 based on a least square method, outputting an exponential model and exponential model parameters; The fourth module: inputting the exponential model parameters into a power function model related to the load rate, and outputting power function model parameters; Fifth module: set the load rate to 100%, based on the power function model and the power function model parameters, calculate the temperature rise stability value and time constant under 100% transformer rated current I e . The sixth module: based on GB / T1094.12 standard, outputting winding average temperature rise, and comparing with the maximum allowable temperature rise value to evaluate the actual capacity and carrying capacity of the transformer.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the two-stage short-time small current based dry-type transformer capacity rapid evaluation method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to realize the steps of the two-stage short-time small current based dry-type transformer capacity rapid evaluation method according to any one of claims 1 to 6.

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