CN109858066B - Over-temperature early warning method and system for converter - Google Patents
Over-temperature early warning method and system for converter Download PDFInfo
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- CN109858066B CN109858066B CN201811424858.5A CN201811424858A CN109858066B CN 109858066 B CN109858066 B CN 109858066B CN 201811424858 A CN201811424858 A CN 201811424858A CN 109858066 B CN109858066 B CN 109858066B
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Abstract
The invention provides a method and a system for pre-warning over-temperature of a converter, wherein the method comprises the following steps: modeling: obtaining a temperature change model of the current transformer according to historical operation parameter data of the current transformer, wherein the temperature change model simulates the relation between the temperature parameter and other parameters except the temperature parameter in the operation parameters of the current transformer; the measuring and calculating steps are as follows: transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter; judging: and judging whether the converter is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the converter. The over-temperature early warning method and the over-temperature early warning system for the converter can accurately judge whether the converter is over-temperature or not.
Description
Technical Field
The invention relates to the field of converters, in particular to a converter over-temperature early warning method and system.
Background
Wind energy is taken as a clean renewable energy source, and is increasingly valued by countries around the world, and the strategy of new energy in China has focused on the development of wind power generation. The converter is one of core components in the wind power generation system, and failure of the converter can directly lead to stop of the wind power generator, so that great economic loss is caused. Over-temperature of the converter is one of main faults of the converter, and how to predict the over-temperature in advance so as to solve the problem of avoiding fault shutdown and reducing economic loss in time is an industry concern.
At present, a temperature threshold tthr is set in a common mode of coping with the overtemperature early warning of the converter, and an alarm is triggered when the temperature reaches the threshold tthr. In another mode, the temperature average value tavg of the full-field converter is calculated, the temperature tr of the converter is compared with the temperature average value tavg, and the over-temperature state is judged according to the difference value tdelta.
The technology of setting the temperature threshold value is dead, the threshold value is set too high, the temperature is often not processed until reaching the early warning value, false alarm is easily caused when the threshold value is set too low, and the normal fluctuation of the temperature in different seasons and different geographic positions is difficult to deal with.
The defect is that by comparing the temperature of the converter with the average value of the temperature of the full-field converter:
1. when the number of converters is too small, even a single converter, the average value is meaningless.
2. The distribution area of wind power generators in a general wind power plant is very wide, the local temperature and wind power in each area are different, the local temperature difference can be accumulated to the deviation tdelta between the temperature of the converter to be tested and the temperature average value of the full-field converter, particularly in the wind power change stage, the output power change moment of each wind power generator is different (the influence of the generated power on the temperature of the converter is great), the rising and falling steps of the temperature of the converter are inconsistent, the difference between the current temperature of the converter to be tested and the temperature average value of the full-field converter is also influenced, and erroneous judgment is easy to cause.
The two schemes for coping with the over-temperature early warning mode of the converter have no data visualization part, the judging means is single, and the misjudgment rate is high.
Disclosure of Invention
The invention aims to provide a converter over-temperature early warning method and a system, which are used for solving the technical problems of single judgment means and high misjudgment rate of the converter over-temperature early warning method in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an overtemperature early warning method for a converter comprises the following steps:
modeling: obtaining a temperature change model of the current transformer according to historical operation parameter data of the current transformer, wherein the temperature change model simulates the relation between the temperature parameter and other parameters except the temperature parameter in the operation parameters of the current transformer;
the measuring and calculating steps are as follows: transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter;
judging: and judging whether the converter is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the converter.
Further, the over-temperature warning method of the converter further comprises the following steps:
and a display step: and displaying a real-time temperature curve and temperature alarm information of the converter.
Further, the modeling step includes:
collecting historical data of operation parameters of the converter under the normal operation condition;
cleaning the collected historical data of the operation parameters of the converter;
and excavating the cleaned data by using a machine learning algorithm to obtain a temperature change model under the condition of normal operation of the converter.
Further, cleaning the collected historical data of the operation parameters of the converter comprises removing invalid data, reserving valid data and converting a data format.
Further, in the judging step, when the deviation value of the expected temperature and the temperature parameter of the converter exceeds the set threshold range, the converter is judged to be over-heated.
An over-temperature warning system for a converter, comprising:
the model generation module is used for obtaining a temperature change model of the current transformer according to historical operation parameter data of the current transformer, and the temperature change model simulates the relation between the temperature parameter and other parameters except the temperature parameter in the operation parameters of the current transformer;
the calculation module is used for transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter;
and the judging module is used for judging whether the converter is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the converter.
Further, the converter over-temperature early warning system further comprises:
the display module is used for displaying the real-time temperature curve and the temperature alarm information of the converter to a user,
further, the model generation module includes:
the data acquisition unit is used for acquiring historical data of the operation parameters of the acquisition converter under the normal operation condition;
the data processing unit is used for cleaning the collected historical data of the operation parameters of the converter;
the machine learning unit is used for excavating the cleaned data by utilizing a machine learning algorithm to obtain a temperature change model of the converter under the normal running condition.
Further, the data processing unit cleans the collected historical data of the converter operation parameters, including removing invalid data, retaining valid data and converting data formats.
Further, when the deviation value of the expected temperature and the temperature parameter of the converter exceeds the set threshold range, the judging module judges that the converter is over-heated.
Compared with the prior art, the method and the system for pre-warning the over-temperature of the current transformer utilize the machine learning technology in artificial intelligence to obtain the temperature change model of the current transformer according to the historical operation parameter data of the current transformer, can more accurately match the curve of the temperature change along with other parameters of the equipment, transfer other parameters except the temperature parameter in the current real-time operation parameters of the current transformer into the temperature change model for calculation to obtain the expected temperature of the current transformer, judge whether the current transformer is over-temperature according to the deviation value of the expected temperature and the temperature parameter of the current transformer, and can improve the judgment accuracy.
Drawings
Fig. 1 is a flowchart of a method for warning about over-temperature of a converter according to an embodiment of the present invention.
Fig. 2 is a specific flowchart of step S1 in fig. 1.
Fig. 3 is a schematic structural diagram of an over-temperature warning system of a converter according to an embodiment of the invention.
Fig. 4 is a schematic structural diagram of the model generating module in fig. 3.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, an embodiment of the present invention provides a method for early warning of an overtemperature of a converter, which includes steps S1 to S4, and are described below.
Step S1, modeling: and obtaining a temperature change model of the current transformer according to the historical operation parameter data of the current transformer, wherein the temperature change model simulates the relation between the temperature parameter and other parameters except the temperature parameter in the operation parameters of the current transformer.
When the converter operates, operation data of the converter can be collected in real time during the monitoring of the converter, and the collected data can be stored in a database. The operation parameters of the converter comprise equipment number, time stamp, power grid active power, power grid reactive power, module temperature, power grid AB line voltage effective value, power grid BC line voltage effective value, power grid CA line voltage effective value, power grid A phase current effective value, power grid B phase current effective value, power grid C phase current effective value, direct current side voltage, direct current side current, direct current side power, power grid frequency, bus voltage actual measurement value, MPPT target power, power factor, rated power and system state machine. The historical operation parameter data of the converter is obtained from the database, and the temperature change model under the condition of normal operation of the converter can be obtained by training the historical operation parameter data of the converter by using an artificial intelligence machine learning algorithm.
Specifically, step S1 includes:
step S11: collecting historical data of operation parameters of the converter under the normal operation condition;
step S12: cleaning the collected historical data of the operation parameters of the converter;
step S13: and excavating the cleaned data by using a machine learning algorithm to obtain a temperature change model under the condition of normal operation of the converter.
In step S12, cleaning the collected historical data of the operating parameters of the converter includes removing invalid data, retaining valid data, and converting a data format.
Step S2, measuring and calculating: and transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter.
In step S2, the current real-time operation parameters of the current transformer are obtained, and other parameters except the temperature parameters are transmitted into the temperature change model for calculation, so that the expected temperature of the current transformer can be obtained, and the expected temperature is the temperature which should be used when the current transformer normally operates.
Step S3, judging: and judging whether the converter is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the converter.
When the deviation value of the expected temperature and the temperature parameter of the converter exceeds the set threshold range, the temperature deviation is larger, and the converter is judged to be over-temperature, so that an alarm is given. When the deviation value of the expected temperature and the temperature parameter of the current transformer is in the set threshold range, the current temperature of the current transformer is not greatly deviated from the normal operation temperature of the current transformer, and the current transformer is judged to be in normal operation.
Step S4, displaying: and displaying a real-time temperature curve and temperature alarm information of the converter.
When the temperature of the converter is monitored, the temperature of the converter needs to be displayed in real time, and when the converter is over-heated, alarm information is displayed, so that monitoring staff can know the real-time temperature of the converter in real time, and timely find the alarm information to perform fault treatment.
As shown in fig. 3, in the embodiment of the present invention, there is further provided a converter over-temperature early warning system, which includes a model generating module 21, a calculating module 22, a judging module 23 and a display module 24. The model generating module 21 is configured to derive a temperature change model of the current transformer according to historical operation parameter data of the current transformer, where the temperature change model simulates a relationship between a temperature parameter and other parameters except the temperature parameter in the operation parameters of the current transformer. The calculation module 22 is configured to transmit parameters other than the temperature parameter in the current real-time operation parameters of the current transformer to the temperature change model for calculation, so as to obtain the expected temperature of the current transformer. The judging module 23 is configured to judge whether the current transformer is over-heated according to the deviation value of the expected temperature and the temperature parameter of the current transformer, and when the deviation value of the expected temperature and the temperature parameter of the current transformer exceeds a set threshold range, the judging module 23 judges that the current transformer is over-heated. The display module 24 is used for displaying the real-time temperature curve and the temperature alarm information of the converter to a user,
further, as shown in fig. 4, the model generation module 21 includes a data acquisition unit 221, a data processing unit 222, and a machine learning unit 223. The data acquisition unit 221 is configured to acquire historical data of operation parameters of the acquisition converter under a normal operating condition. The data processing unit 222 is configured to clean the collected historical data of the operation parameters of the converter, and the data processing unit cleans the collected historical data of the operation parameters of the converter, including removing invalid data, complementing missing data, and converting data formats. The machine learning unit 223 is configured to utilize a machine learning algorithm to mine the cleaned data, so as to obtain a temperature change model of the converter under the normal operation condition.
In summary, by adopting the method and the system for pre-warning the over-temperature of the current transformer, the temperature change model of the current transformer is obtained according to the historical operation parameter data of the current transformer by utilizing the machine learning technology in artificial intelligence, the curve of the temperature change along with other parameters of the equipment can be more accurately matched, other parameters except the temperature parameter in the current real-time operation parameters of the current transformer are transmitted into the temperature change model for calculation, the expected temperature of the current transformer is obtained, whether the current transformer is over-temperature or not is judged according to the deviation value of the expected temperature and the temperature parameter of the current transformer, and the judgment accuracy can be improved.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. The over-temperature early warning method for the converter is characterized by comprising the following steps of:
modeling: when the converter operates, operation data of the converter are acquired in real time during the monitoring of the converter, the acquired data are stored in a database, historical operation parameter data of the converter are acquired from the database, the historical operation parameter data of the converter are trained by using an artificial intelligence machine learning algorithm, a temperature change model under the condition of normal operation of the converter is obtained, and the temperature change model simulates the relation between temperature parameters and other parameters except the temperature parameters in the operation parameters of the converter;
the measuring and calculating steps are as follows: transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter; judging: judging whether the current transformer is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the current transformer;
the historical operation parameters of the converter comprise equipment numbers, time stamps, active power of a power grid, reactive power of the power grid, module temperature, effective voltage value of an AB line of the power grid, effective voltage value of a BC line of the power grid, effective voltage value of a CA line of the power grid, effective current value of a A phase of the power grid, effective current value of a B phase of the power grid, effective current value of a C phase of the power grid, direct current side voltage, direct current side current, direct current side power, power grid frequency, actual measurement value of bus voltage, MPPT target power, power factor, rated power and a system state machine.
2. The method for warning against excessive temperature of a converter according to claim 1, further comprising: and a display step: and displaying a real-time temperature curve and temperature alarm information of the converter.
3. The method for warning against excessive temperature of a converter according to claim 1, wherein said modeling step comprises: collecting historical data of operation parameters of the converter under the normal operation condition; cleaning the collected historical data of the operation parameters of the converter; and excavating the cleaned data by using a machine learning algorithm to obtain a temperature change model under the condition of normal operation of the converter.
4. The method of claim 3, wherein cleaning the collected historical data of the converter operating parameters includes removing invalid data, retaining valid data, and converting a data format.
5. The method for warning about excessive temperature of a current transformer according to claim 1, wherein in the step of determining, when the deviation value between the expected temperature and the temperature parameter of the current transformer exceeds a set threshold range, the current transformer is determined to be excessive.
6. An overtemperature early warning system for a converter, comprising:
the model generation module is used for obtaining a temperature change model of the converter according to historical operation parameter data of the converter, wherein the temperature change model simulates the relation between the temperature parameter and other parameters except the temperature parameter in the operation parameters of the converter, and the historical operation parameters of the converter comprise equipment numbers, time stamps, power grid active power, power grid reactive power, module temperature, power grid AB line voltage effective value, power grid BC line voltage effective value, power grid CA line voltage effective value, power grid A phase current effective value, power grid B phase current effective value, power grid C phase current effective value, direct current side voltage, direct current side power, power grid frequency, bus voltage actual measurement value, MPPT target power, power factors, rated power and a system state machine;
the calculation module is used for transmitting other parameters except the temperature parameter in the current real-time operation parameters of the current converter into the temperature change model for calculation to obtain the expected temperature of the current converter;
and the judging module is used for judging whether the converter is over-heated or not according to the deviation value of the expected temperature and the temperature parameter of the converter.
7. The converter over-temperature warning system of claim 6, further comprising: and the display module is used for displaying the real-time temperature curve and the temperature alarm information of the converter to a user.
8. The converter over-temperature warning system of claim 6, wherein the model generation module comprises:
the data acquisition unit is used for acquiring historical data of the operation parameters of the acquisition converter under the normal operation condition;
the data processing unit is used for cleaning the collected historical data of the operation parameters of the converter;
the machine learning unit is used for excavating the cleaned data by utilizing a machine learning algorithm to obtain a temperature change model of the converter under the normal running condition.
9. The converter over-temperature warning system of claim 8, wherein the data processing unit cleans collected historical data of converter operating parameters including removing invalid data, retaining valid data and data format conversion.
10. The system of claim 6, wherein the determining module determines that the converter is over-temperature when the deviation of the expected temperature from the temperature parameter of the converter exceeds a set threshold range.
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