CN117272701B - Transformer temperature prediction model and method based on meteorological environment data - Google Patents
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Abstract
The invention discloses a transformer temperature prediction model and a method based on meteorological environment data, which relate to the technical field of transformer temperature prediction, and the method comprises the following steps: the method and the device can scientifically predict the change trend of the transformer temperature according to the meteorological environment data, monitor the temperature relative to a large number of sensors, reduce the number of the sensors and maintenance work, reduce cost and workload, solve the problem of damage or shutdown of the transformer caused by interference of environment and working conditions, reduce economic loss caused by faults, and further provide reliable support guarantee for safe and stable operation of the transformer.
Description
Technical Field
The invention relates to the technical field of transformer temperature prediction, in particular to a transformer temperature prediction model and method based on meteorological environment data.
Background
Transformer temperature prediction is a technique for monitoring and predicting the temperature during operation of a transformer. Because the temperature of the transformer has important influence on the performance and the service life of the transformer, accurately monitoring and predicting the temperature of the transformer can help operators to take measures in time, and the normal operation and the safety of the transformer are ensured.
In conventional transformer temperature monitoring, temperature sensors are typically used to measure the temperature of various parts of the transformer in real time. However, this approach has some limitations: at present, the temperature of a transformer is measured through a temperature sensor, a large number of sensors are required to be arranged, if the temperature of each part of the transformer is monitored in a whole coverage manner, the cost and maintenance difficulty of equipment are increased, meanwhile, the equipment is possibly interfered by the environment and working conditions, the condition that the temperature data of the transformer is inaccurate or cannot be obtained is caused, and the transformer is damaged.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a transformer temperature prediction model and a transformer temperature prediction method based on meteorological environment data, which can effectively solve the problems related to the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: a transformer temperature prediction model and method based on meteorological environment data comprises the following steps: s1, acquiring meteorological environment monitoring data, wherein the meteorological environment monitoring data comprise environmental temperature, humidity, wind speed and altitude; s2, analyzing the temperature of the transformer based on the change of the environmental temperature in the meteorological environment monitoring data, predicting the temperature of the transformer at different environmental temperatures, analyzing the temperature of the transformer based on the change of the humidity in the meteorological environment monitoring data, predicting the temperature of the transformer at different humidity, analyzing the temperature of the transformer based on the change of the wind speed in the meteorological environment monitoring data, predicting the temperature of the transformer at different wind speeds, analyzing the temperature of the transformer based on the change of the altitude in the meteorological environment monitoring data, and predicting the temperature of the transformer at different altitudes; s3, analyzing the temperature of the transformer based on meteorological environment monitoring data to obtain predicted values of the temperature of the transformer under different environment temperatures, humidity, wind speeds and altitudes, and establishing a linear regression equation of the temperature prediction of the transformer; s4, evaluating the transformer temperature prediction coincidence coefficient by using the real data, evaluating whether a transformer temperature prediction linear regression equation fits the real data or not based on the calculated transformer temperature prediction coincidence coefficient, and optimizing the transformer temperature prediction linear regression equation if the transformer temperature prediction linear regression equation cannot fit the real data.
Further, the transformer temperature is analyzed based on the change of the environmental temperature in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different environmental temperatures is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the ambient temperature to a proper reference value, and recording the current initial ambient temperature by using an infrared thermometerRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an environmental temperature control device, and proportionally regulating the environmental temperature to obtain the monitoring temperature regulating times +.>And is numbered->And record the current test ambient temperature +.>At each current test ambient temperature +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment temperature +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:
predicted value representing the temperature of the transformer at the test ambient temperature,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test ambient temperature, < >>Indicating the ambient initial temperature, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the heat capacity of the transformer->Representing the volume of the transformer>Representing the temperature coefficient.
Further, the transformer temperature is analyzed based on the humidity change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different humidity is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the humidity in the environment to a proper reference value, and recording the initial humidity of the current environment by using a hygrometer measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an environmental humidity control device, and regulating the environmental humidity in equal proportion to obtain the monitoring humidity regulating times +.>And is numbered->And recording the current test environment humidity +.>Humidity at each current test environment +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment humidity +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows: />,/>Predictive value representing the temperature of the transformer under test ambient humidity,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test environmental humidity, < >>Indicating the initial humidity of the environment, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the heat capacity of the transformer->Representing the volume of the transformer>Represents the coefficient of humidity change, ">Indicating the loss factor of iron at ambient humidity, < >>The loss factor under the humidity of the copper environment is shown.
Further, the transformer temperature is analyzed based on the wind speed change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different wind speeds is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the wind speed in the environment to a proper reference value, and recording the initial wind speed of the current environment by using a wind speed measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the The environmental wind speed control device is preset to regulate the environmental wind speed in equal proportion to obtain the monitoring wind speed regulating times +.>And is numbered->And record the current test environment wind speed +.>Wind speed at each current test environment>Turning on the transformer to operate for a period of timeTo stabilize its temperature, wind speed for the test environment>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows: />,Predicted value representing the temperature of the transformer at the test ambient wind speed,/->Indicating the initial temperature of the transformer, < >>Represent the firstSecondary test of ambient wind speed, < >>Indicating the ambient initial wind speed,/-, and%>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the wind-variation coefficient, +.>Loss coefficient of iron at ambient wind speed, < >>Loss coefficient at copper ambient wind speed.
Further, the altitude change in the meteorological environment monitoring dataThe transformer temperature is analyzed, and the specific process of predicting the transformer temperature at different altitudes is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; placing the transformer at a proper altitude and recording the initial altitudeRecording the initial temperature of the transformer using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an altitude control device, and proportionally adjusting the altitude to obtain the monitoring altitude adjustment times +.>And is numbered->And record the current test altitude +.>At each current test altitude +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test altitude +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:,/>representing the temperature of the transformer at the test altitudePredictive value->Indicating the initial temperature of the transformer, < >>Indicate->Subtest altitude,/->Representing the initial altitude of the sea,representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the altitude change factor.
Further, the analysis is performed on the transformer temperature based on the meteorological environment monitoring data to obtain the predicted value of the transformer temperature under different environment temperatures, humidity, wind speed and altitude, and the calculation formula for establishing the linear regression equation of the transformer temperature prediction is as follows:wherein->Predictive value representing the temperature of the transformer in the test weather environment,/-, for example>、/>、/>、/>、/>Representing regression coefficients->Represents the intercept (I)>Predicted value representing the temperature of the transformer at the test ambient temperature,/->Predictive value representing the temperature of the transformer under test ambient humidity,/->Predicted value representing the temperature of the transformer at the test ambient wind speed,/->Representing a predicted value of the transformer temperature at the test altitude.
Further, the specific process of evaluating the transformer temperature prediction compliance coefficient using the real data is as follows: placing a specified transformer in a set testing environment comprising ambient temperature, humidity, altitude and altitude, ensuring normal and stable working state and parameters, keeping constant current input so as to keep the load of the transformer unchanged, and measuring the temperature of the transformer by using an infrared thermometer; placing the appointed transformer in a set test environment, and testing the appointed transformer for multiple times, wherein the times of each measurement are as followsNumber->Under each current test environment, the transformer is opened to run for a period of time to be stableDetermining the temperature of the transformer, and recording the actual temperature of the transformer at the environmental test temperature by using an infrared thermometer>And establishing a linear regression equation of the temperature prediction of the transformer based on meteorological environment monitoring data to obtain the predicted temperature ++of the transformer in the test environment>Calculating the compliance coefficient of the transformer temperature prediction according to the compliance coefficient>The calculation formula is as follows:wherein->Expressed as a transformer temperature prediction compliance coefficient, +.>Expressed as transformer adapted temperature difference, < >>Expressed as transformer temperature corresponds to +.>Predictive value of secondary test->Expressed as transformer temperature corresponds to +.>Actual value of secondary test,/->The correction factor indicated as the set temperature prediction, e, is indicated as a natural constant.
Further, the method evaluates the linear regression of the transformer temperature prediction based on the coincidence coefficient of the calculated transformer temperature predictionThe specific procedure for whether the procedure fits the real data is as follows: coincidence coefficient based on calculation of transformer temperature predictionComparing actual temperature data of the transformer with predicted temperature data of the transformer, if the predicted compliance coefficient of the transformer is smaller than or equal to a preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature can be better fit to the actual data, and if the predicted compliance coefficient of the transformer is larger than the preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature cannot be better fit to the actual data.
Further, if the transformer temperature prediction linear regression equation cannot fit the real data, the specific process of optimizing the transformer temperature prediction linear regression equation is as follows: by adjusting parameters of the modelOptimizing a model, and establishing a transformer temperature prediction linear regression equation based on meteorological environment monitoring data to obtain a predicted temperature of the transformer in a test environment>Multiple data tests are performed to test +.>The value of (2) is more accurate, reduce +.>And->Difference between the two, let the compliance coefficient of the transformer temperature prediction +.>The temperature of the transformer is more close to the preset temperature of the transformer to meet the coefficient threshold; based on the data test, the parameters->Random sampling is performed to determine the parameter->And determining how many times of parameter searching is required, randomly sampling parameter combinations in a parameter space according to the set searching times, training a model on a training set for each randomly sampled parameter combination, evaluating the value of a target model on a verification set, recording the parameter combination for obtaining the optimal target function value in the searching process, and taking the parameter combination with the optimal target function value as the optimal parameter after all parameter searching is completed.
The transformer temperature prediction model based on the meteorological environment data is constructed by adopting a transformer temperature prediction method based on the meteorological environment data.
The invention has the following beneficial effects:
(1) According to the model and the method for predicting the temperature of the transformer based on the meteorological environment data, the change trend of the temperature of the transformer is predicted, the number of sensors and maintenance work can be reduced, the cost and the workload are reduced, the damage and the shutdown of the transformer caused by the interference of the environment and the working condition are avoided, and the economic loss caused by faults is reduced.
(2) The transformer temperature prediction model and the transformer temperature prediction method based on the meteorological environment data can help to optimize energy scheduling and operation management of the power system, reasonably utilize the meteorological environment prediction result, reduce unnecessary energy consumption, reduce carbon emission and environmental load, and achieve the aims of energy conservation and emission reduction.
(3) According to the model and the method for predicting the temperature of the transformer based on the meteorological environment data, the temperature change trend of the transformer is predicted, the transformer is kept to work in a proper temperature range, and the efficiency and the reliability of equipment are improved.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
FIG. 1 is a flow chart of the steps of the method of the present invention.
FIG. 2 is a flow chart of the steps for testing the temperature of the transformer based on the change of the environmental temperature in the meteorological environment monitoring data.
FIG. 3 is a flow chart showing the steps of testing the temperature of the transformer based on the change of the environmental humidity in the meteorological environment monitoring data.
FIG. 4 is a flow chart of the steps for testing the temperature of the transformer based on the change in the ambient wind speed in the meteorological environment monitoring data.
FIG. 5 is a flow chart of the steps for testing the temperature of the transformer based on the change in altitude in the meteorological environment monitoring data.
Fig. 6 is a flowchart illustrating a correction procedure based on a linear regression equation for predicting the temperature of the transformer.
Detailed Description
According to the transformer temperature prediction model and method based on the meteorological environment data, the problem of predicting the transformer temperature based on the meteorological environment monitoring data is solved.
The problems in the embodiments of the present application are as follows:
referring to fig. 1, the implementation of the present invention provides the following technical solutions: a transformer temperature prediction model and method based on meteorological environment data comprises the following steps: s1, acquiring meteorological environment monitoring data, wherein the meteorological environment monitoring data comprise environmental temperature, humidity, wind speed and altitude.
In this embodiment, quality inspection of the acquired weather-environment monitoring data is performed, including verifying the accuracy, integrity and consistency of the data. Excluding outliers or erroneous data that may be present.
S2, analyzing the temperature of the transformer based on the change of the environmental temperature in the meteorological environment monitoring data, predicting the temperature of the transformer at different environmental temperatures, analyzing the temperature of the transformer based on the change of the humidity in the meteorological environment monitoring data, predicting the temperature of the transformer at different humidity, analyzing the temperature of the transformer based on the change of the wind speed in the meteorological environment monitoring data, predicting the temperature of the transformer at different wind speeds, analyzing the temperature of the transformer based on the change of the altitude in the meteorological environment monitoring data, and predicting the temperature of the transformer at different altitudes.
Specifically, referring to fig. 2, the transformer temperature is analyzed based on the change of the environmental temperature in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature at different environmental temperatures is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the ambient temperature to a proper reference value, and recording the current initial ambient temperature by using an infrared thermometerRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an environmental temperature control device, and proportionally regulating the environmental temperature to obtain the monitoring temperature regulating times +.>And is numbered->And record the current test ambient temperature +.>At each current test ambient temperature +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment temperature +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows: />，/>Predicted value representing the temperature of the transformer at the test ambient temperature,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test ambient temperature, < >>Indicating the ambient initial temperature, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the heat capacity of the transformer->Representing the volume of the transformer>Representing the temperature coefficient.
In this embodiment, in the formula、/>、/>、/>、/>、/>All values measured before the start of the experiment and are constant; the set test environment of the transformer is as follows: the temperature, humidity, wind speed and altitude in the test environment are all in a proper range; the infrared thermometer is connected with the data recording equipment, and the recording of the temperature data of the transformer means: the correct sampling frequency is set, and the change of the temperature of the transformer can be accurately recorded; the step of homogenizing the predicted value of the transformer temperature is as follows: the data is scaled to a specified range by linear mapping for data processing using a min-max scaling method.
Specifically, referring to fig. 3, the transformer temperature is analyzed based on the humidity change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature at different humidity is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the humidity in the environment to a proper reference value, and recording the initial humidity of the current environment by using a hygrometer measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an environmental humidity control device, and regulating the environmental humidity in equal proportion to obtain the monitoring humidity regulating times +.>And is numbered->And recording the current test environment humidity +.>Humidity at each current test environment +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment humidity +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows: />,/>Predictive value representing the temperature of the transformer under test ambient humidity,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test environmental humidity, < >>Indicating the initial humidity of the environment, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Representing transportLine time->Representing the heat capacity of the transformer->Representing the volume of the transformer>Represents the coefficient of humidity change, ">Indicating the loss factor of iron at ambient humidity, < >>The loss factor under the humidity of the copper environment is shown.
In this embodiment, the preset usage environment humidity control device means: setting the humidity control device to an appropriate target humidity threshold range; in the formula、/>、/>、/>、/>、/>All values measured before the start of the experiment and are constant; the set test environment of the transformer is as follows: the temperature, humidity, wind speed and altitude in the test environment are all in a proper range; the infrared thermometer is connected with the data recording equipment, and the recording of the temperature data of the transformer means: the correct sampling frequency is set, and the change of the temperature of the transformer can be accurately recorded; variable pressureThe homogenization of the predicted value of the temperature refers to: the data is scaled to a specified range by linear mapping for data processing using a min-max scaling method.
Specifically, referring to fig. 4, the transformer temperature is analyzed based on the wind speed change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature at different wind speeds is as follows: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; adjusting the wind speed in the environment to a proper reference value, and recording the initial wind speed of the current environment by using a wind speed measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the The environmental wind speed control device is preset to regulate the environmental wind speed in equal proportion to obtain the monitoring wind speed regulating times +.>And is numbered->And record the current test environment wind speed +.>Wind speed at each current test environment>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, wind speed for the test environment>Homogenizing the predicted value of the temperature of the down-converterThe formula is as follows: />,/>Predicted value representing the temperature of the transformer at the test ambient wind speed,/->Indicating the initial temperature of the transformer, < >>Indicate->Secondary test of ambient wind speed, < >>Indicating the ambient initial wind speed,/-, and%>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the wind-variation coefficient, +.>Loss coefficient of iron at ambient wind speed, < >>Loss coefficient at copper ambient wind speed.
In this embodiment, the preset usage environment wind speed control device means: setting the wind speed control device to an appropriate target wind speed threshold range; in the formula、/>、/>、/>All values measured before the start of the experiment and are constant; the set test environment of the transformer is as follows: the temperature, humidity, wind speed and altitude in the test environment are all in a proper range; the infrared thermometer is connected with the data recording equipment, and the recording of the temperature data of the transformer means: the correct sampling frequency is set, and the change of the temperature of the transformer can be accurately recorded; the step of homogenizing the predicted value of the transformer temperature is as follows: the data is scaled to a specified range by linear mapping for data processing using a min-max scaling method.
Specifically, referring to fig. 5, the analysis of the transformer temperature based on the change of altitude in the meteorological environment monitoring data predicts the following specific process of the transformer temperature at different altitudes: placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged; placing the transformer at a proper altitude and recording the initial altitudeRecording the initial temperature of the transformer using an infrared thermometer>The method comprises the steps of carrying out a first treatment on the surface of the Presetting an altitude control device, and proportionally adjusting the altitude to obtain the monitoring altitude adjustment times +.>And is numbered->And record the current test altitude +.>At each current test altitude +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test altitude +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows: />,/>Predicted value representing the temperature of the transformer at the test altitude, < >>Indicating the initial temperature of the transformer, < >>Indicate->Subtest altitude,/->Representing the initial altitude,/->Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the altitude change factor.
In this embodiment, the preset use of the altitude control means: setting the altitude control device to an appropriate target wind speed threshold range; in the formula、/>、/>、/>All values measured before the start of the experiment and are constant; the set test environment of the transformer is as follows: the temperature, humidity, wind speed and altitude in the test environment are all in a proper range; the infrared thermometer is connected with the data recording equipment, and the recording of the temperature data of the transformer means: the correct sampling frequency is set, and the change of the temperature of the transformer can be accurately recorded; the step of homogenizing the predicted value of the transformer temperature is as follows: the data is scaled to a specified range by linear mapping for data processing using a min-max scaling method.
S3, analyzing the temperature of the transformer based on meteorological environment monitoring data to obtain predicted values of the temperature of the transformer under different environment temperatures, humidity, wind speeds and altitudes, and establishing a linear regression equation of the temperature prediction of the transformer.
Specifically, the temperature of the transformer is analyzed based on meteorological environment monitoring data to obtain the predicted value of the temperature of the transformer under different environment temperatures, humidity, wind speed and altitude, and the calculation formula for establishing the linear regression equation of the temperature prediction of the transformer is as follows:wherein->Predictive value representing the temperature of the transformer in the test weather environment,/-, for example>、/>、/>、/>、/>Representing regression coefficients->Represents the intercept (I)>Predicted value representing the temperature of the transformer at the test ambient temperature,/->Predictive value representing the temperature of the transformer under test ambient humidity,/->Predicted value representing the temperature of the transformer at the test ambient wind speed,/->Representing a predicted value of the transformer temperature at the test altitude.
In the embodiment, the linear regression equation of the temperature prediction of the transformer is that a scatter diagram is drawn and a straight line is fitted through multiple measurements to present an image of a model; wherein in the equationThe value of (2) is calculated from the results of a plurality of experiments, and the value represents the ambient temperatureDegree of influence of degree, humidity, wind speed and altitude on transformer temperature.
S4, evaluating the transformer temperature prediction coincidence coefficient by using the real data, evaluating whether a transformer temperature prediction linear regression equation fits the real data or not based on the calculated transformer temperature prediction coincidence coefficient, and optimizing the transformer temperature prediction linear regression equation if the transformer temperature prediction linear regression equation cannot fit the real data.
Specifically, referring to fig. 6, using the real data, a specific procedure for evaluating the transformer temperature prediction compliance coefficient is as follows: placing a specified transformer in a set testing environment comprising ambient temperature, humidity, altitude and altitude, ensuring normal and stable working state and parameters, keeping constant current input so as to keep the load of the transformer unchanged, and measuring the temperature of the transformer by using an infrared thermometer; placing the appointed transformer in a set test environment, and testing the appointed transformer for multiple times, wherein the times of each measurement are as followsNumber->Under each current testing environment, opening the transformer, allowing the transformer to run for a period of time to stabilize the temperature, using an infrared thermometer, and recording the actual temperature of the transformer at the environmental testing temperature +.>And establishing a linear regression equation of the temperature prediction of the transformer based on meteorological environment monitoring data to obtain the predicted temperature ++of the transformer in the test environment>Calculating the compliance coefficient of the transformer temperature prediction according to the compliance coefficient>The calculation formula is as follows:wherein->Expressed as a transformer temperature prediction compliance coefficient, +.>Expressed as transformer adapted temperature difference, < >>Expressed as transformer temperature corresponds to +.>Predictive value of secondary test->Expressed as transformer temperature corresponds to +.>Actual value of secondary test,/->The correction factor indicated as the set temperature prediction, e, is indicated as a natural constant.
In this embodiment, the parameters are changed under different environmental conditions, and the temperature prediction correction factor is usedThe method is used for adjusting and correcting the functions of various factors and parameters, improving the accuracy of data and the accuracy of prediction, enabling the system design to be more in line with actual conditions, and the transformer is used in the set test environment: the temperature, humidity, wind speed and altitude in the test environment are all in a proper range; the infrared thermometer is connected with the data recording equipment, and the recording of the temperature data of the transformer means: the correct sampling frequency is set, and the change of the temperature of the transformer can be accurately recorded.
Specifically, based on the coincidence coefficient of the calculated transformer temperature prediction, the specific process of evaluating whether the transformer temperature prediction linear regression equation fits the real data is as follows: based on calculationsCompliance coefficient for transformer temperature predictionComparing actual temperature data of the transformer with predicted temperature data of the transformer, if the predicted compliance coefficient of the transformer is smaller than or equal to a preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature can be better fit to the actual data, and if the predicted compliance coefficient of the transformer is larger than the preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature cannot be better fit to the actual data.
In this embodiment, performing data processing means: comparing and analyzing the prediction result of the linear regression model with the actual transformer temperature, drawing a scatter diagram between the prediction result and the actual value, and observing the trend and deviation condition of the scatter diagram.
Specifically, if the transformer temperature prediction linear regression equation cannot fit the real data, the specific process of optimizing the transformer temperature prediction linear regression equation is as follows: by adjusting parameters of the modelOptimizing a model, and establishing a transformer temperature prediction linear regression equation based on meteorological environment monitoring data to obtain a predicted temperature of the transformer in a test environment>Multiple data tests are performed to test +.>The value of (2) is more accurate, reduce +.>And->Difference between the two, let the compliance coefficient of the transformer temperature prediction +.>The temperature of the transformer is more close to the preset temperature of the transformer to meet the coefficient threshold; based on the data test, the parameters->Random sampling is performed to determine the parameter->And determining how many times of parameter searching is required, randomly sampling parameter combinations in a parameter space according to the set searching times, training a model on a training set for each randomly sampled parameter combination, evaluating the value of a target model on a verification set, recording the parameter combination for obtaining the optimal target function value in the searching process, and taking the parameter combination with the optimal target function value as the optimal parameter after all parameter searching is completed.
In this embodiment, the multiple data tests refer to: judging whether the independent variable and the temperature are in linear relation or not by observing a scatter diagram, fitting a linear equation, and adjusting parametersIs a value of (2); the parameter values in the random parameters are in the experimental test parameter range and the like, so that the specific test significance of the parameter values is ensured.
The transformer temperature prediction model based on the meteorological environment data is constructed by adopting a transformer temperature prediction method based on the meteorological environment data.
In summary, the present application has at least the following effects: according to the transformer temperature prediction model and the transformer temperature prediction method based on the meteorological environment data, the change trend of the transformer temperature can be predicted according to the meteorological environment monitoring data, the number of the sensors and maintenance work can be reduced compared with a large number of sensors, cost and workload are reduced, damage or shutdown of the transformer caused by interference of environment and working conditions is avoided, economic loss caused by faults is reduced, and reliable support guarantee is provided for safe and stable operation of the transformer.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of systems, apparatuses (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (5)
1. The transformer temperature prediction method based on the meteorological environment data is characterized by comprising the following steps of:
s1, acquiring meteorological environment monitoring data, wherein the meteorological environment monitoring data comprise environmental temperature, humidity, wind speed and altitude;
s2, analyzing the temperature of the transformer based on the change of the environmental temperature in the meteorological environment monitoring data, predicting the temperature of the transformer at different environmental temperatures, analyzing the temperature of the transformer based on the change of the humidity in the meteorological environment monitoring data, predicting the temperature of the transformer at different humidity, analyzing the temperature of the transformer based on the change of the wind speed in the meteorological environment monitoring data, predicting the temperature of the transformer at different wind speeds, analyzing the temperature of the transformer based on the change of the altitude in the meteorological environment monitoring data, and predicting the temperature of the transformer at different altitudes;
s3, analyzing the temperature of the transformer based on meteorological environment monitoring data to obtain predicted values of the temperature of the transformer under different environment temperatures, humidity, wind speeds and altitudes, and establishing a linear regression equation of the temperature prediction of the transformer;
s4, evaluating a transformer temperature prediction coincidence coefficient by using the real data, evaluating whether a transformer temperature prediction linear regression equation fits the real data or not based on the calculated transformer temperature prediction coincidence coefficient, and optimizing the transformer temperature prediction linear regression equation if the transformer temperature prediction linear regression equation cannot fit the real data;
the method comprises the steps of analyzing the temperature of a transformer based on meteorological environment monitoring data to obtain predicted values of the temperature of the transformer under different environment temperatures, humidity, wind speed and altitude, and establishing a calculation formula of a linear regression equation of the temperature prediction of the transformer as follows:
wherein the method comprises the steps ofRepresenting transformers under test weather conditionsPredicted value of temperature>、/>、/>、/>、/>The regression coefficient is represented as a function of the regression coefficient,represents the intercept (I)>Predicted value representing the temperature of the transformer at the test ambient temperature,/->Predictive value representing the temperature of the transformer under test ambient humidity,/->Predicted value representing the temperature of the transformer at the test ambient wind speed,/->A predicted value representing the temperature of the transformer at the test altitude;
the concrete process for evaluating the transformer temperature prediction coincidence coefficient by using the real data is as follows:
placing a specified transformer in a set testing environment comprising ambient temperature, humidity, altitude and altitude, ensuring normal and stable working state and parameters, keeping constant current input so as to keep the load of the transformer unchanged, and measuring the temperature of the transformer by using an infrared thermometer;
placing the appointed transformer in a set test environment, and testing the appointed transformer for multiple times, wherein the times of each measurement are as followsNumber->Under each current testing environment, opening the transformer, allowing the transformer to run for a period of time to stabilize the temperature, using an infrared thermometer, and recording the actual temperature of the transformer at the environmental testing temperature +.>And establishing a linear regression equation of the temperature prediction of the transformer based on meteorological environment monitoring data to obtain the predicted temperature ++of the transformer in the test environment>Calculating the compliance coefficient of the transformer temperature prediction according to the compliance coefficient>The calculation formula is as follows:
wherein the method comprises the steps ofExpressed as a transformer temperature prediction compliance coefficient, +.>Expressed as transformer adapted temperature difference, < >>Expressed as transformer temperature corresponds to +.>Predictive value of secondary test->Expressed as transformer temperature corresponds to +.>Actual value of secondary test,/->A correction factor expressed as a set temperature prediction, e expressed as a natural constant;
the specific process for evaluating whether the transformer temperature prediction linear regression equation fits real data based on the calculated transformer temperature prediction coincidence coefficient is as follows:
coincidence coefficient based on calculation of transformer temperature predictionComparing actual temperature data of the transformer with predicted temperature data of the transformer, if the predicted compliance coefficient of the transformer is smaller than or equal to a preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature can be better fit to the actual data, and if the predicted compliance coefficient of the transformer is larger than the preset threshold value of the predicted compliance coefficient of the transformer, the linear regression equation of the transformer temperature cannot be better fit to the actual data;
if the transformer temperature prediction linear regression equation cannot fit the real data, the specific process of optimizing the transformer temperature prediction linear regression equation is as follows:
by adjusting parameters of the modelOptimizing a model, and establishing a transformer temperature prediction linear regression equation based on meteorological environment monitoring data to obtain a predicted temperature of the transformer in a test environment>Multiple data tests are performed to test +.>The value of (2) is more accurate, reduce +.>And->Difference between the two, let the compliance coefficient of the transformer temperature prediction +.>The temperature of the transformer is more close to the preset temperature of the transformer to meet the coefficient threshold;
based on data testing, parameters ofRandom sampling is performed to determine the parameter->And determining how many times of parameter searching is required, randomly sampling parameter combinations in a parameter space according to the set searching times, training a model on a training set for each randomly sampled parameter combination, evaluating the value of a target model on a verification set, recording the parameter combination for obtaining the optimal target function value in the searching process, and taking the parameter combination with the optimal target function value as the optimal parameter after all parameter searching is completed.
2. The method for predicting the temperature of a transformer based on meteorological environment data according to claim 1, wherein: the transformer temperature is analyzed based on the change of the environmental temperature in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different environmental temperatures is as follows:
placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged;
adjusting the ambient temperature to a proper reference value, and recording the current initial ambient temperature by using an infrared thermometerRecording the initial temperature of the transformer by using an infrared thermometer>；
Presetting an environmental temperature control device, and proportionally adjusting the environmental temperature to obtain the monitoring temperature adjustment timesAnd is numbered->And record the current test ambient temperature +.>At each current test ambient temperature +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment temperature +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:
predicted value representing the temperature of the transformer at the test ambient temperature,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test ambient temperature, < >>Indicating the ambient initial temperature, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the heat capacity of the transformer->Representing the volume of the transformer>Representing the temperature coefficient.
3. The method for predicting the temperature of a transformer based on meteorological environment data according to claim 2, wherein: the transformer temperature is analyzed based on the humidity change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different humidity is as follows:
placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged;
adjusting the humidity in the environment to a proper reference value, and recording the initial humidity of the current environment by using a hygrometer measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>；
The environmental humidity control device is preset to regulate the environmental humidity in equal proportion to obtain the monitoring humidity regulation timesAnd is numbered->And recording the current test environment humidity +.>Humidity at each current test environment +.>Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test environment humidity +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:
predictive value representing the temperature of the transformer under test ambient humidity,/->Indicating the initial temperature of the transformer, < >>Indicate->Sub-test environmental humidity, < >>Indicating the initial humidity of the environment, +.>Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the heat capacity of the transformer->Representing the volume of the transformer>Represents the coefficient of humidity change, ">Indicating the loss factor of iron at ambient humidity, < >>The loss factor under the humidity of the copper environment is shown.
4. A method for predicting the temperature of a transformer based on meteorological environment data as claimed in claim 3, wherein: the transformer temperature is analyzed based on the wind speed change in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different wind speeds is as follows:
placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged;
adjusting the wind speed in the environment to a proper reference value, and recording the initial wind speed of the current environment by using a wind speed measuring toolRecording the initial temperature of the transformer by using an infrared thermometer>；
The environmental wind speed control device is preset to regulate the environmental wind speed in equal proportion to obtain the monitoring wind speed regulation timesAnd is numbered->And record the current test environment wind speed +.>Wind speed at each current test environment>Turning on the variable voltageA device for allowing it to operate for a period of time +.>To stabilize its temperature, wind speed for the test environment>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:
predicted value representing the temperature of the transformer at the test ambient wind speed,/->Indicating the initial temperature of the transformer, < >>Indicate->Secondary test of ambient wind speed, < >>Indicating the ambient initial wind speed,/-, and%>Representing current input, +.>Representing the resistance of the transformer,indicating the run time +.>Representing the wind-variation coefficient, +.>Loss coefficient of iron at ambient wind speed, < >>Loss coefficient at copper ambient wind speed.
5. The method for predicting the temperature of a transformer based on meteorological environment data of claim 4, wherein: the transformer temperature is analyzed based on the change of the altitude in the meteorological environment monitoring data, and the specific process of predicting the transformer temperature under different altitudes is as follows:
placing a specified transformer in a set test environment, ensuring that the specified transformer has normal and stable working states and parameters, measuring the temperature of the transformer by using an infrared thermometer, and keeping constant current input so as to keep the load of the transformer unchanged;
placing the transformer at a proper altitude and recording the initial altitudeRecording the initial temperature of the transformer using an infrared thermometer>；
Presetting an altitude control device, and proportionally adjusting the altitude to obtain the adjustment times of the monitored altitudeAnd is numbered->And record the current test altitude +.>At each time whenFront test altitude->Turning on the transformer to operate for a period of time +.>To stabilize its temperature, for the test altitude +.>And carrying out homogenization treatment on the predicted value of the temperature of the lower transformer, wherein the treatment formula is as follows:
predicted value representing the temperature of the transformer at the test altitude, < >>Indicating the initial temperature of the transformer, < >>Indicate->Subtest altitude,/->Representing the initial altitude,/->Representing current input, +.>Representing the resistance of the transformer, < >>Indicating the run time +.>Representing the altitude change factor.
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