Quick dry-type transformer capacity evaluation method and system based on two-section short-time small current

Abstract

The invention belongs to the field of electrical engineering, and relates to a dry-type transformer capacity rapid assessment method and system based on a two-section short-time small current, and the method comprises the steps: inputting a first section of small current I1 to a winding of a transformer, and collecting the winding temperature data T (t) 1 of the first section until a steady state is reached; under the condition that the power supply is not interrupted, the current is directly increased to a second section of small current I2, and the winding temperature data T (t) 2 of the second section is continuously collected until the stable state is reached again; fitting the winding temperature data T (t) 1 and T (t) 2, and outputting an index model and index model parameters; inputting the index model parameters into a power function model related to the load rate, and outputting power function model parameters; setting the load rate to be 100%, and calculating to obtain a temperature rise stable value and a time constant under the 100% rated current Ie of the transformer; and based on the GB / T1094.12 standard, comparing the average temperature rise of the winding with the maximum allowable temperature rise value, and evaluating the actual capacity and bearing capacity of the transformer. The device has the effects of saving energy, reducing consumption and improving efficiency.

Description

Technical Field

[0001] This application belongs to the field of electrical engineering, and particularly relates to a method and system for quickly evaluating the capacity of dry-type transformers based on two-stage short-time small current. Background Technique

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

[0003] According to the provisions of the standard of GB / T 1094.11-2022 "Power Transformers - Part 11: Dry-Type Transformers", the stable value at 100% rated current should be less than 1 kA, while the stable values at 40% and 60% rated current should be less than 0.4 kA and 0.6 kA respectively. According to the provisions of the standard of IEC 60076-11 "Power Transformers - Part 11: Dry-Type Transformers", the stable value at 100% rated current should be less than 1.25 kA, while the stable values at 40% and 60% 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, especially in terms of power supply capacity limitations and test time.

[0005] Limitations of existing technical means:

[0006] Power supply capacity limitation: When conducting a load temperature rise test on-site, it is often difficult to meet the large current required for the test due to insufficient power supply capacity, especially in remote areas or small substations. According to GB / T1094.11-2022, when the input test current is lower than the rated current I N , but not lower than 90%I N , after the core and winding temperatures have both reached stability, the winding temperature rise Δθ N is measured using the I t resistance method, and it is corrected to the temperature rise Δθ N under rated load according to the given formula. In short, the standard test current shall not be lower than 90% of the rated current. When the input test current is lower than the rated current I N , but not lower than 90%I N , although the winding temperature rise Δθ t can be measured using the resistance method and corrected to the temperature rise Δθ N, but the on-site power supply capacity often fails to meet this requirement, resulting in the inability to conduct the test smoothly or deviation in the test results.

[0007] Long test time: The temperature rise test may need to last for dozens of hours, which not only prolongs the power outage time, affects the stability of the power system, but also may cause unnecessary losses to the transformer.

[0008] To improve the accuracy of the temperature rise test, the method and device for rapid temperature rise prediction of transformers that map small currents to large currents (CN 117849494B) propose a method of a three-stage deduction calculation model. This method obtains the temperature rise data sets of the transformer at different load rates, including the first steady-state temperature rise value, the temperature rise rate, and the second steady-state temperature rise value, and then uses a preset mathematical function model fitting strategy to determine the change of the temperature rise data of the transformer at different load rates. This method also includes verifying the temperature rise data to correct the change of the temperature rise data, thereby improving the accuracy of the prediction. Although the three-stage method has advantages in terms of accuracy, its operation process is relatively complex and the time consumption is relatively long.

[0009] Therefore, improvement is needed. Summary of the Invention

[0010] To achieve energy conservation, consumption reduction, and efficiency improvement, the present application provides a method and system for rapid evaluation of the capacity of dry-type transformers based on two-stage short-time small currents.

[0011] The first object of the invention of the present application is achieved through the following technical solutions:

[0012] A method for rapid evaluation of the capacity of dry-type transformers based on two-stage short-time small currents, comprising the steps of:

[0013] Input the first-stage small current I into the winding of the transformer 1 , where the first-stage small current I 1 is 40% of the rated current I of the transformer e , and collect the winding temperature data T(t) of the first stage 1 until reaching a steady state;

[0014] Without interrupting the power supply, directly increase the current to the second-stage small current I 2 , where the second-stage small current I 2 is 60% of the rated current I of the transformer e , and continue to collect the winding temperature data T(t) of the second stage 2 until reaching a steady state again;

[0015] Based on the least squares method, fit the winding temperature data T(t) 1 , T(t) 2 to output an exponential model and exponential model parameters;

[0016] Input the exponential model parameters into the power function model related to the load rate, and output the power function model parameters;

[0017] Set the load rate to 100%, and calculate the stable temperature rise value and time constant at 100% of the transformer rated current I e under;

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

[0019] In a preferred embodiment, without interrupting the power supply, directly increase the current to the second small current I 2 , the second small current I 2 is 60% of the transformer rated current I e , and continue to collect the winding temperature data T(t) of the second segment 2 until reaching the steady state again, including the steps:

[0020] Without interrupting the power supply, directly adjust the current of the transformer winding from I 1 to I 2 , I 1 =0.4·I e , I 2 =0.6·I e , and collect the winding temperature data T(t) of the second segment 2 ;

[0021] Calculate the temperature difference ΔT between the i-th winding temperature data and the (i-1)-th winding temperature data 2 and the corresponding time difference Δt 2 ;

[0022] Based on the preset formula Output the average temperature change rate V 2 ;

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

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

[0025] For a load rate of 40%, based on the least squares formula Fit the collected winding temperature data T(t) of the first segment 1 to output the exponential model Y 1 = a 40％ (1 - exp(-t / b 40％ ), the steady-state temperature rise value a 40％ , and the time constant b 40％ ;

[0026] For a load rate of 60%, based on a 60％ = T(t) b , m = Vρc p , the pre-measured Vρc p , deduce to output the time constant b 60％ .

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

[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 steady-state temperature rise value and time constant at 100% of the transformer rated current I e includes steps:

[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, calculate the stable value a of the temperature rise 100％ , and the time constant b 100％ .

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

[0034] Output the average temperature rise of the output winding based on the GB / T1094.12 standard The maximum allowable temperature rise value T max ;

[0035] Based on a 100％ , calculate the average temperature rise T of the winding avg , and compare it with the maximum allowable 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 load-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 usage capacity needs to be reduced.

[0038] The above object two of the present application is achieved by the following technical solutions:

[0039] A rapid evaluation system for the capacity of a dry-type transformer based on two-stage short-time small current includes:

[0040] The first module: Input the first-stage small current I into the winding of the transformer 1 , and the first-stage small current I 1 is 40% of the rated current I of the transformer e , and collect the winding temperature data T(t) of the first stage 1 until it reaches a steady state;

[0041] The second module: Without interrupting the power supply, directly increase the current to the second-stage small current I 2 , and the second-stage small current I 2 is 60% of the rated current I of the transformer e , and continue to collect the winding temperature data T(t) of the second stage 2 until it reaches a steady state again;

[0042] The third module: Based on the least squares method, for the winding temperature data T(t) 1 , T(t)2 Perform fitting and output the exponential model and exponential model parameters;

[0043] The fourth module: Input the exponential model parameters into the power function model related to the load rate and output the power function model parameters;

[0044] The fifth module: Set the load rate to 100%, and based on the power function model and the power function model parameters, calculate the stable temperature rise value and time constant at 100% of the transformer rated current I e below;

[0045] The sixth module: Based on the GB / T1094.12 standard, output the average winding temperature rise, compare it with the maximum allowable temperature rise value, and evaluate the actual capacity and load-carrying capacity of the transformer.

[0046] The above-mentioned third object of the present application is achieved by the following technical solutions:

[0047] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for quickly evaluating the capacity of a dry-type transformer based on two-stage short-time small current are implemented.

[0048] The above-mentioned fourth object of the present application is achieved by the following technical solutions:

[0049] A computer-readable storage medium stores a computer program, characterized in that when the computer program is executed by a processor, the steps of the above-mentioned method for quickly evaluating the capacity of a dry-type transformer based on two-stage short-time small current are implemented.

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

[0051] An innovative test method is implemented. This method sequentially inputs short-time small currents I 1 、I 2 and the transformer rated current I e, while continuously monitoring the temperature change of the winding until the system reaches a steady state. This process can obtain the stable temperature rise values and time constants at different load rates of 40% and 60%. 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 stable temperature rise value and time constant at the rated current of the transformer. In addition, this 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 at the rated current. This test method replaces the traditional short-circuit temperature rise test that takes 15 to 20 hours, greatly improving the test efficiency. 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, based on the GB / T1094.12 standard, the average temperature rise of the winding is evaluated and compared with the maximum allowable temperature rise value to accurately evaluate the actual capacity and load-bearing capacity of the transformer and ensure its safe and reliable operation. This method not only improves the test efficiency and the accuracy of the results but also significantly enhances the practicality and economy of the entire evaluation process by adopting efficient test means. Description of the Drawings

[0052] Figure 1 is the implementation flowchart of a method for rapidly evaluating the capacity of a dry-type transformer based on two-stage short-time small current in this application;

[0053] Figure 2 is the dynamic temperature rise change curve of the hot spot of the transformer winding at different load rates (40%, 60%);

[0054] Figure 3 is the schematic diagram of the two-stage continuous short-time small-current temperature rise test;

[0055] Figure 4 is an implementation flowchart of step S40 in an embodiment of a method for rapidly evaluating the capacity of a dry-type transformer based on two-stage short-time small current in this application;

[0056] Figure 5 is an implementation flowchart of step S50 in an embodiment of a method for rapidly evaluating the capacity of a dry-type transformer based on two-stage short-time small current in this application;

[0057] Figure 6 is an implementation flowchart of step S60 in an embodiment of a method for rapidly evaluating the capacity of a dry-type transformer based on two-stage short-time small current in this application;

[0058] Figure 7 is a principle block diagram of a computer device in this application. Detailed implementation manners

[0059] The following further describes this application in detail with reference to the attached Figure 1-7 drawings.

[0060] In one embodiment, as Figure 1 shown, this application discloses a method for quickly evaluating the capacity of a dry-type transformer based on two-stage short-time small current, which specifically includes the following steps:

[0061] S10: Input the first-stage small current I 1 to the winding of the transformer. The first-stage small current I 1 is 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;

[0062] S20: Without interrupting the power supply, directly increase the current to the second-stage small current I 2 . The second-stage small current I 2 is 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;

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

[0064] S40: Input the exponential model parameters into a power function model related to the load rate to output power function model parameters;

[0065] S50: Set the load rate to 100%, and based on the power function model and power function model parameters, calculate the steady-state temperature rise value and time constant at 100% of the rated current I e of the transformer;

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

[0067] In this embodiment, an innovative test method is implemented. This method sequentially inputs short-time small currents I 1 , I 2 and the rated current I e of the transformer to the transformer winding., while continuously monitoring the temperature change of the winding until the system reaches a steady state. This process can obtain the stable temperature rise values and time constants at different load rates of 40% and 60%. 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 stable temperature rise value and time constant at the rated current of the transformer.

[0068] In addition, this 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 at the rated current. This test method replaces the traditional short-circuit temperature rise test that takes 15 to 20 hours, greatly improving the test efficiency. 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. This not only improves the economy of the test but also reduces energy consumption.

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

[0070] Such as Figure 2 , step S20 includes the steps:

[0071] S201: Without interrupting the power supply, directly adjust the current of the transformer winding from I 1 to I 2 , I 1 = 0.4·I e , I 2 = 0.6·I e , and collect the winding temperature data T(t) 2 of the second segment;

[0072] S202: Calculate the temperature difference ΔT 2 between the i-th winding temperature data and the (i - 1)-th winding temperature data, as well as the corresponding time difference Δt 2 ;

[0073] S203: Based on the preset formula output the average temperature change rate V 2 ;

[0074] S204: When the average temperature change rate V 2 of 10 consecutive winding temperature data is less than the preset threshold ε, determine the winding temperature data T(t)2 Reach a steady state and output the second-stage temperature rise steady value T(t). b .

[0075] In this embodiment, step S20 directly adjusts the 40% rated current I of the transformer to 60% rated current I of the transformer without interrupting the power supply e , and continue to apply this current I to the transformer winding e , and collect temperature data in real time based on a high-precision thermocouple. Subsequently, calculate the temperature difference ΔT 2 between adjacent temperature data points 2 and the time difference Δt 2 , and output the average temperature change rate V based on a preset formula 2 . When the average temperature change rate V of 10 consecutive winding temperature data 2 is less than the preset threshold ε, it is determined that the winding temperature T(t) 2 has reached a steady state, and the second-stage temperature rise steady value T(t) is output b . This method ensures a smooth transition of the load rate, avoids temperature fluctuations caused by power-off and restart, provides continuous and accurate temperature data, and provides a reliable basis for evaluating the temperature rise characteristics of the transformer under high load conditions

[0076] For example Figure 3 , step S30 includes the steps of

[0077] S301: For a load rate of 40%, based on the least squares formula , fit the collected winding temperature data T(t) 1 of the first stage, and output the exponential model Y 1 =a 40％ (1 - exp(-t / b 40％ ), the temperature rise steady value a 40％ , and the time constant b 40％ ;

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

[0079] In this embodiment, step S30 fits the temperature time series at a load of 40% by the least squares method and outputs the exponential model Y 1 =a 40％ (1 - exp(-t / b40％ )) and the stable temperature rise value a 40％ , the time constant b 40％ . Based on a 60％ , m = Vρc p , the pre-measured Vρc p , determine the time constant b at a load rate of 60% 60％ .

[0080] For example Figure 4 , step S40 includes the 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, by inputting the corresponding stable temperature rise values into the power function model at two different load rates of 40% and 60%, the thermal response characteristics of the transformer are fitted. Steps SA1 and SA2 respectively process the data input at different load rates, and step SA3 calculates the parameters of the power function model based on these inputs. The effect of this method is that it can effectively quantify the thermal time constant and temperature rise rate of the transformer, thereby realizing a rapid and accurate assessment of the transformer capacity. In this way, not only the scientificity and systematicness of the assessment process are improved, but also the assessment results have high accuracy and practicality, which helps to ensure the stable operation of the transformer and extend its service life.

[0085] For example Figure 5 , step S50 includes the 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％ , the 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 steady-state temperature rise value and time constant of the transformer at a load rate of 100% are calculated. Step S501 specifically realizes this process by comprehensively inputting all relevant parameters into the power function model a N =nx m 、b N =px r , and then calculating the steady-state temperature rise value a 100％ and time constant b 100％ . The effect of this method is that it can accurately simulate the thermal behavior of the transformer under actual working conditions, providing an important basis for evaluating the long-term operation performance of the transformer. In this way, not only can the thermal stable state of the transformer be obtained quickly, but also the accuracy of the evaluation results is improved, which helps to predict the overheating risk of the transformer, ensure the safe operation and design optimization of the transformer, and at the same time provides reliable data support for the maintenance and fault diagnosis of the transformer.

[0088] For example Figure 6 , step S60 includes the steps of:

[0089] S601: Based on the GB / T1094.12 standard, output the average temperature rise of the output winding The maximum allowable temperature rise value T max ;

[0090] S602: Based on a 100％ , calculate the average temperature rise T of the winding avg , and compare it with the maximum allowable temperature rise value T max ;

[0091] S603: 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;

[0092] S604: When T avg >T max , it is considered that the transformer cannot withstand the rated capacity of the transformer and the operating capacity needs to be reduced.

[0093] In this embodiment, the core of step S60 is to judge the operating state of the transformer by monitoring and calculating the average temperature rise of the transformer winding and comparing it with the specified maximum allowable temperature rise value. S601: Based on the national standard GB / T1094.12, output the average temperature rise of the output winding The maximum allowable temperature rise value T max。These standard parameters are important bases to ensure that the transformer meets the requirements in terms of safety and performance. S602: Using the stable value a of the temperature rise monitored in real time 100％ , calculate the average winding temperature rise T avg . This is accomplished by measuring the temperature change of the transformer at a load rate of 100%. When the condition of S603 is satisfied, that is, the average winding 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 load-bearing capacity meet the requirements. If the condition of S604 is established, that is, the average winding temperature rise T avg is greater than the maximum allowable temperature rise value T max , this indicates that the transformer cannot withstand its rated capacity and the operating capacity needs to be reduced to prevent overheating. This method thus provides a preventive measure, which helps to extend the service life of the transformer and ensure the stable operation of the power system.

[0094] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0095] In one embodiment, a rapid dry-type transformer capacity evaluation system based on two-stage short-time small current is provided. This rapid dry-type transformer capacity evaluation system based on two-stage short-time small current corresponds one-to-one with the rapid dry-type transformer capacity evaluation method based on two-stage short-time small current in the above embodiment. This rapid dry-type transformer capacity evaluation system based on two-stage short-time small current includes:

[0096] The first module: Input the first-stage small current I 1 to the winding of the transformer. The first-stage small current I 1 is 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] The second module: Without interrupting the power supply, directly increase the current to the second-stage small current I 2 . The second-stage small current I 2 is 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: Based on the least squares method, fit the winding temperature data T(t) 1 and T(t) 2 , and output the exponential model and exponential model parameters;

[0099] Fourth module: Input the exponential model parameters into the power function model related to the load rate, and output the power function model parameters;

[0100] Fifth module: Set the load rate to 100%, and calculate the steady-state temperature rise value and time constant of 100% rated current I of the transformer based on the power function model and the power function model parameters; e under the temperature rise;

[0101] Sixth module: Based on the GB / T1094.12 standard, output the average winding temperature rise, compare it with the maximum allowable temperature rise value, and evaluate the actual capacity and load-bearing capacity of the transformer.

[0102] Optionally, it further includes:

[0103] First acquisition module: Without interrupting the power supply, directly adjust the current of the transformer winding from I 1 to I 2 , I 1 = 0.4·I e , I 2 = 0.6·I e , and collect the winding temperature data T(t) of the second segment 2 ;

[0104] First calculation module: Calculate the temperature difference ΔT between the i-th winding temperature data and the (i - 1)-th winding temperature data 2 and the corresponding time difference Δt 2 ;

[0105] First output module: Output the average temperature change rate V based on the preset formula 2 ;

[0106] Second output module: When the average temperature change rate V 2 of 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 the steady-state temperature rise value T(t) of the second segment is output b .

[0107] Optionally, it further includes:

[0108] Third output module: For a load rate of 40%, fit the collected winding temperature data T(t) of the first segment based on the least squares formula 1 , and output the exponential model Y 1 = a 40％ (1 - exp(-t / b 40％ )) and the steady-state temperature rise value a 40％, time constant b 40％ ;

[0109] Fourth output module: For a load factor of 60%, based on a 60％ = T(t) b , m = Vρc p , pre-measured Vρc p , derive output time constant b 60％ .

[0110] Optionally, it further includes:

[0111] First input module: When the load factor is 40%, input N = 40%, x = 0.4 into the power function model a N = nx m , b N = px r ;

[0112] Second input module: When the load factor is 60%, input N = 60%, x = 0.6 into the power function model a N = nx m , b N = px r ;

[0113] Fifth output module: Based on SA1 - SA2, output the model parameters n, m, p, r.

[0114] Optionally, it further includes:

[0115] Third calculation module: When the load factor 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 value of temperature rise a 100％ , time constant b 100％ .

[0116] Optionally, it further includes:

[0117] Eighth output module: Based on the GB / T1094.12 standard, output the average winding temperature rise the maximum allowable temperature rise T max ;

[0118] First module: Based on a 100％ , calculate the average winding temperature rise T avg , and compare it with the maximum allowable temperature rise 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] The second judgment module: When T avg >T max it is considered that the transformer cannot withstand the rated capacity of the transformer, and the operating capacity needs to be reduced.

[0121] For the specific limitations of a rapid dry-type transformer capacity evaluation system based on two-stage short-time small current, reference can be made to the limitations of a rapid dry-type transformer capacity evaluation method based on two-stage short-time small current in the above text, which will not be elaborated here. Each module in the above rapid dry-type transformer capacity evaluation system based on two-stage short-time small current can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0122] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 7 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, 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 operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the temperature rise stability value and the time constant. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a rapid dry-type transformer capacity evaluation method based on two-stage short-time small current.

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

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

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

[0126] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A method for rapid capacity assessment of dry-type transformers based on two-stage short-term low current, characterized in that: Includes steps: A first small current I1 is input to the transformer winding, and the first small current I1 is the transformer 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 increased to the second small current I2, which is the rated current I of the transformer. e 60% of the winding temperature, and continue to collect the second section of winding temperature data T(t)2 until a steady state is reached again; Fit the winding temperature data T(t)1 and T(t)2 based on the least squares method, and output the exponential model and exponential model parameters; Inputting the exponential model parameters into a power function model related to the load rate, and outputting the power function model parameters; Set the load rate to 100%, and calculate the 100% transformer rated current I based on the power function model and power function model parameters. e Temperature rise stability value and time constant under the condition of Based on GB / T1094.12 standard, the average temperature rise and maximum allowable temperature rise of the output winding are calculated, and the average temperature rise of the winding is compared with the maximum allowable temperature rise to evaluate the actual capacity and load-bearing capacity of the transformer.

2. A method for rapid capacity assessment of dry-type transformers based on two-stage short-time and small current according to claim 1, characterized in that: Without interrupting the power supply, the current is directly increased to the second small current I2, and the second small current I2 is the rated current I of the transformer. e The step of collecting the winding temperature data T(t)2 of the second segment until a 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 collect the winding temperature data T(t)2 of the second section; 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; Based on preset formula Output average temperature change rate V2; When the average temperature change rate V2 of 10 consecutive winding temperature data is less than the preset threshold ε, it is judged that the winding temperature data T(t)2 has reached a steady state, and the second temperature rise stable value T(t) is output. b .

3. The method for rapid capacity assessment of dry-type transformers based on two-stage short-time and small current according to claim 1 is characterized in that: The step of fitting the winding temperature data T(t)1 and T(t)2 based on the least squares method and outputting an exponential model and exponential model parameters comprises the following steps: For a load factor of 40%, based on the least squares formula Fit the collected first section of winding temperature data T(t)1, and output the exponential model Y1=a 40％ (1-exp(-t / b 40％ )) Temperature rise stability value a 40％ , time constant b 40％ ; For a load factor of 60%, based on a 60％ =T(t) b , m=Vρc p , pre-measured Vρc p ,roll out Output time constant b 60％ .

4. The method for rapid capacity assessment of dry-type transformer based on two-stage short-time small current according to claim 1 is characterized in that: 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: SA1: When the load rate is 40%, N = 40%, x = 0.4 is input into the power function model SA2: When the load factor is 60%, N = 60%, x = 0.6 is input into the power function model SA3: Based on SA1-SA2, output model parameters n, m, p, r.

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

6. A method for rapid dry-type transformer capacity assessment based on two-stage short-time small current according to claim 1, characterized in that: The steps of evaluating the actual capacity and carrying capacity of the transformer by outputting the average temperature rise of the winding based on the GB / T1094.12 standard and comparing it with the maximum allowable temperature rise value include the following steps: Based on GB / T1094.12 standard, the average temperature rise of the output winding Maximum allowable temperature rise T max ; based on a 100％ , calculate the average winding temperature rise T avg and the maximum allowable temperature rise T max Compare; When T avg ≤T max When the transformer is considered to be able to bear the rated capacity of the transformer, the actual capacity and carrying capacity meet the requirements; When T avg >T max When the transformer is considered unable to bear the rated capacity of the transformer, the capacity needs to be reduced.

7. A dry-type transformer capacity rapid assessment system based on two-stage short-time small current, characterized in that: include: The first module: input the first small current I1 to the transformer winding, wherein the first small current I1 is the rated current I of the transformer. e 40% and collect the winding temperature data T(t)1 of the first section until a steady state is reached; The second module: without interrupting the power supply, the current is directly increased to the second small current I2, and the second small current I2 is the rated current I of the transformer. e 60% of the winding temperature, and continue to collect the second section of winding temperature data T(t)2 until a steady state is reached again; The third module: Fit the winding temperature data T(t)1 and T(t)2 based on the least squares method, and output the exponential model and exponential model parameters; The fourth module: inputting the exponential model parameters into the power function model related to the load rate, and outputting the power function model parameters; The fifth module: Set the load rate to 100%, and calculate the 100% transformer rated current I based on the power function model and power function model parameters. e Temperature rise stability value and time constant under the condition of Module 6: Based on GB / T1094.12 standard, the average temperature rise of the output winding is compared with the maximum allowable temperature rise value to evaluate the actual capacity and load-bearing 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: When the processor executes the computer program, the steps of a method for rapid dry-type transformer capacity assessment based on two-stage short-time and small current as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a method for rapid dry-type transformer capacity assessment based on two-stage short-time and small current as described in any one of claims 1 to 6 are implemented.

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