Method for The Networked Monitoring of At Least One Transformer

Abstract

The invention relates to a method for networked monitoring of at least one transformer (5), wherein the following steps/stages are performed: receiving (110) an electromagnetic signal (210) by a monitoring component (20) at the active transformer (5), the signal (210) being specific to at least one transformer parameter of the transformer (5), carrying out a frequency evaluation (120) based on the received signal (210) by the monitoring component (20), outputting (130) monitoring information (240) about a result of the frequency evaluation (120) to a network (70) for transmission to a processing system (80) for evaluation (140) of the transformer parameter based on the monitoring information (240).

Claims

1. A method for networked monitoring of at least one transformer, wherein the following is performed: receiving an electromagnetic signal by a monitoring component at the active transformer, the signal being specific to at least one transformer parameter of the transformer, carrying out a frequency evaluation based on the received signal by the monitoring component, outputting monitoring information about a result of the frequency evaluation to a network for transmission to a processing system for evaluating the transformer parameter based on the monitoring information.

2. The method according to claim 1, wherein the frequency evaluation is implemented as a Fourier transform by which the received signal is decomposed into its frequency components in order to carry out the evaluation of the transformer parameter on the basis of the frequency components.

3. The method according to claim 1, wherein the monitoring component is structurally separate from the transformer and the processing system.

4. The method according to claim 1, wherein the signal is generated in the form of an electromagnetic field by the transformer during operation, the monitoring component being arranged at least spatially on the transformer at a distance from the transformer within reception range of the signal.

5. The method according to claim 1, wherein the signal is implemented as a low frequency signal.

6. The method according to claim 1, wherein the following is carried out to evaluate the at least one transformer parameter: receiving the output monitoring information by the processing system, performing a process of the received monitoring information by an evaluation element to use a result of the processing as information about the transformer parameter.

7. The method according to claim 6, wherein the evaluation elements has at least one neural network to perform the process in accordance with machine learning on the basis of a learned information of the evaluation elements.

8. The method according to claim 6, wherein the transformer parameter is implemented as an electrical parameter of the transformer, in order to perform the process at least for measuring current at the transformer for detecting a load profile of the transformer.

9. The method according to claim 6, wherein the following is carried out at least before or during or after the output: detecting a time information about a time of receiving the signal by the monitoring component, associating the time information with the monitoring information to output the monitoring information with the associated time information, performing the process based on the time information).

10. The method according to claim 1, wherein the frequency evaluation is carried out for frequencies at least in the range from 10 Hz to 100 Hz in order to carry out the evaluation of the transformer parameter likewise on the basis of specific frequency components in this range.

11. The method according to claim 1, wherein at least the carrying out of the frequency evaluation or the evaluation of the transformer parameter are carried out in real time.

12. The method according to claim 1, wherein a state of the transformer is monitored during operation.

13. The method according to claim 1, wherein the network is at least partially implemented as the internet.

14. A monitoring component for networked monitoring of at least one transformer, comprising: a receiving component for receiving an electromagnetic signal at the active transformer, wherein the signal is specific to at least one transformer parameter of the transformer, an evaluation component for carrying out a frequency evaluation on the basis of the received signal, an output component for outputting monitoring information about a result of the frequency evaluation to a network for transmission to a processing system for evaluation of the transformer parameter based on the monitoring information.

15. A monitoring component according to claim 14, wherein the receiving component has a receiving antenna which is configured to receive the signal as a low frequency signal.

16. A system for networked monitoring of at least one transformer, comprising: a monitoring component according to claim 14, the processing system for evaluating the transformer parameter based on the monitoring information.

17. The system according to claim 16, wherein the monitoring component comprises a time component to provide time information about a time interval for the frequency evaluation or about a time of receiving the signal by the monitoring component.

18. The method according to claim 5, wherein the signal is in the frequency range from 40 Hz to 70 Hz, with a frequency of essentially 50 Hz or 60 Hz.

19. The method according to claim 9, wherein the processing is based on sorting the received monitoring information in time based on the associated time information.

20. The monitoring component according to claim 15, wherein the low frequency signal is in the range from 40 Hz to 70 Hz.

Description

[0069] FIG. 1a a schematic diagram for visualizing process steps/stages,

[0070] FIG. 2a schematic representation of parts of a system according to the invention and a monitoring component according to the invention,

[0071] FIG. 3a schematic representation of parts of a monitoring component according to the invention.

[0072] In the following figures, the identical reference signs are used for the same technical features even of different embodiment.

[0073] FIG. 1 schematically visualizes a method according to the invention for networked monitoring of at least one transformer 5. According to a first process step/stage, an electromagnetic signal 210 is received 110 by a monitoring component 20 at a transformer 5. The transformer 5 can be active during the receiving 110 and thus generate the signal 210, for example, during operation. Accordingly, the signal 210 is specific to at least one transformer parameter of the transformer 5. Subsequently, according to a second method step/stage, a frequency evaluation 120 can be carried out by the monitoring component 20 on the basis of the received signal 210. Specifically, a Fast Fourier transform may be used for this purpose so that the frequency evaluation 120 can be carried out by the monitoring component 20 even with low computing power. For example, the monitoring component 20 comprises at least one microcontroller to carry out the frequency evaluation 120. Subsequently, monitoring information 240 about a result of the frequency evaluation 120 may be output to a network 70 at step/stage 130 to transmit the monitoring information 240 to a processing system 80. The processing system 80 may be for evaluating 140 the transformer parameter based on the monitoring information 240.

[0074] Advantageously, this invention can provide full real-time visibility of the transformer 5 power system at exceptionally low equipment and data processing costs.

[0075] Further, the following steps/stages may be performed to carry out the evaluation 140 of the at least one transformer parameter. According to a first step/stage in the evaluation 140, the output monitoring information 240 may be received by the processing system 80. According to a second step/stage in the evaluation 140, a processing 145 of the received monitoring information 240 may be performed by an evaluation means/elements 230 to use a result of the processing 145 as information about the transformer parameter.

[0076] Further, it is possible that a time information 245 about a time of receiving 110 the signal 210 by the monitoring component 20 is acquired. This time information 245 may be associated with the monitoring information 240 to output the monitoring information 240 with the associated time information 245 at step/stage 130. Processing 145 may then be performed based on the time information 245, preferably time sorting the received monitoring information 240 based on the associated time information 245.

[0077] It is also conceivable that the frequency evaluation 120 is implemented as a Fourier transform 120, in particular a fast Fourier transform 120 (FFT), by means of which the received signal 210 is decomposed into its frequency components 250 in order to carry out the evaluation 140 of the transformer parameter on the basis of the frequency components 250

[0078] FIG. 2 schematically shows parts of a monitoring component 20 according to the invention for networked monitoring of at least one transformer 5. A receiving component 21 can be used to receive 110 the electromagnetic signal 210 at the active transformer 5, the signal 210 being specific to at least one transformer parameter of the transformer 5. The receiving component 21 may comprise or be configured as a receiving antenna 21 to receive the signal 210 as a low frequency signal 210, in particular in the range of 40 Hz to 70 Hz. Further, an evaluation component 22 may be provided for carrying out a frequency evaluation 120 based on the received signal 210. An output component 23 may enable output 130 of monitoring information 240 on a result of the frequency evaluation 120 to a network 70 to perform transmission of the monitoring information 240 to a processing system 80.

[0079] Also shown schematically in FIG. 2 is a system according to the invention for networked monitoring of at least one transformer 5, comprising a monitoring component 20 according to the invention and a processing system 80 for evaluating 140 the transformer parameter on the basis of the monitoring information 240. The processing system 80 comprises, for example, at least one server to form a cloud for processing 145. Accordingly, the network 70 may be implemented at least in part as the Internet.

[0080] FIG. 3 shows a monitoring component 20 with further details. The monitoring component 20 and/or the at least one evaluation component 22 or DPU 22 of the monitoring component 20 can each have at least four main sections. In a first main section, a group of one to ten sensors 25 and/or the receiving component 21 and/or the associated interfaces may be provided. In a second main section, a data processing section 26 may carry out frequency evaluation 120 and/or further processing 145. For this purpose, the data processing section 26 may comprise at least one microcontroller and/or integrated circuit. Further, a communication section 27 may be provided as a third main section. The communication section 27 may optionally include a wireless local area network (WLAN) interface and/or a long term evolution (LTE) interface as a data interface to the network 70. The uplink bandwidth for output to the network 70 may be, for example, 150 kbps. The communication section 27 may have the output component 23, which may have a radio interface, in particular a 2.4 GHz radio interface, with a corresponding antenna for output. A fourth main section is formed, for example, by a central clock system 28 that synchronizes the data from the sensors 25 (also with other DPUs) by connecting it to a common atomic clock reference, with which the cloud may also be synchronized. The main sections may be mounted on a common PCB, allowing the monitoring component 20 to form a compact component. In this way, the monitoring component 20 can also be designed/configured to be movable independently of the transformer 5 and, in particular, to be portable by a person. The clock system 28 may have at least one time component such as an oscillator and/or an NTP interface.

[0081] It is possible that the sensors 25 are connected to the data processing section 26 or the microcontroller, for example, via standard I.sup.2C digital interfaces or via analog-to-digital converters or digital audio interfaces. The sensors 25 are configured, for example, to detect at least one of the following sensing parameters: Gas, pressure, light, humidity, temperature, heat (thermal image), vibration (accelerometer), pyroelectric infrared direction detection, electromagnetic interference (EMI), and sound (audio).

[0082] The acquired signal 210 and/or the other acquired acquisition parameters of EMI and/or audio and/or vibration can be further processed in parallel on the evaluation component 22 and in particular the microcontroller with the FFTs (Fast Fourier Transforms) at the same time, if necessary, to achieve an optimal data output of, for example, 1.3 kb per second. This is a very dense data rate that allows accurate frequency and magnitude data of local events to be transmitted to the processing system in real time.

[0083] It has been found that it is advantageous if the frequency evaluation 120 is carried out at the local chip level, i.e. by the evaluation component 22, and thus by the monitoring component 20 locally at the transformer 5 and not remotely therefrom by the processing system 80.

[0084] The at least one other sensor 25 may comprise an EMI sensor that detects a resonant frequency at 50 Hz or 60 Hz. This critical measurement can be calibrated accurately to the energy flowing through the transformer 5. The distance to the transformer 5 can be taken into account. Of particular note here is that no part of the monitoring component 20 needs to be physically connected to the transformer 5.

[0085] The reliability of the monitoring and, in particular, the evaluation 140 of the transformer parameter based on the monitoring information 240 can be further improved and supported if further detection parameters are detected by further sensors 25. The monitoring information 240 may then comprise at least one piece of information about these sensed sensing parameters. This information may also be evaluated by the processing system 80 and, if necessary, compared to the transformer parameter to determine a condition of the transformer 5. In addition to using EMI and audio as possible detection parameters (a transformer 5 makes a low frequency “humming” noise), the use of a vibration in the environment of the transformer 5 may optionally be considered. Mechanical vibrations, which travel slower through surfaces than electromagnetic waves or audio noise through the air, can then be detected as a detection parameter. Since humidity and temperature may also correlate with the condition of transformer 5 and the transformer parameter, respectively, it may also be possible to capture these sensing parameters. These then correlate to form complex data that is precisely synchronous with time and can accurately describe the energy load (EMI) that correlates with the condition of transformer 5.

[0086] When a partial discharge or internal arc occurs in a transformer 5 (i.e., a PD event occurs), both the vibrations, the sounds, and the electromagnetic fields change rapidly. This is usually difficult to detect, and there is no known single “sensor” for partial discharge (PD). In contrast, monitoring information 240, especially if it has additional information not only about the result of frequency evaluation 120 but also about the sensed sensing parameters, can be used to detect such an anomaly. For example, a time history of the monitoring information 240 can also be evaluated for this purpose. If a transformer 5 experiences more than 3 PD events, it is statistically likely to fail. Therefore, a warning message may be outputted when this condition is detected by the evaluation 140.

[0087] Advantageously, machine learning can be used to associate the corresponding monitoring information 240 with a state of the transformer 5. Thus, these anomalies can be detected like TE.

[0088] Further, when the transformer 5 is overloaded, a loud characteristic noise and vibration may occur, which the monitoring component 20 can accurately detect and monitor the processing system 80.

[0089] In addition, for monitoring purposes, the evaluation 140 can be used to locate power transients. Usually, there are at least two low-voltage transformers 5 in each local network in order to be resilient in case of a failure.

[0090] Furthermore, the monitoring component 20 can advantageously measure the actual load of each transformer 5 inductively via EMI, i.e. via the corresponding EMI sensor. Based on the load level, the power demand and power supply (e.g., from distributed generation facilities in industrial areas) in the area of the transformer 5 can be derived in real time. That is, it can be measured whether the actual load on the grid is likely to exceed the physical capacity of the grid. Thus, it provides information about the remaining degree of flexibility in the grid. This remaining degree of flexibility can be calculated as the difference between the actual load and the network capacity. Thus, the monitoring according to the invention facilitates the calculation of the actual degree of flexibility in the network in real time. It may also be possible to use the monitoring to determine the degree of utilization of the network and to derive the degree of flexibility from this value.

[0091] It may be possible for the monitoring component 20, which may be local to the location of the transformer 5 with respect to the transformer 5, to process the data (such as EMI, audio, and vibration) received by the sensors 25 at least partially using a frequency evaluation 120 locally to increase data accuracy. The frequency evaluations 120, if processed correctly over, for example, an hour, may yield a fully accurate calibration of the actual output of the transformer 5 as if measured by a physically connected meter that is still 1 meter or more away.

[0092] In addition, the sensors 25 may also detect temperature and humidity data that changes as production and demand patterns change. Accordingly, the monitoring information 240 may be formed from the signal 210 and the other sensing parameters, and thus may include information about the temperature and humidity at the location of the transformer 5. This combination of data enables, for example, further predictions regarding the future load on the power grid or congestion in the grid.

[0093] The monitoring component 20, and in particular the evaluation component 22, may also enable planning of predictive maintenance by evaluating the monitoring information 240.

[0094] Based on the frequency evaluation 120 and/or the evaluation 140 and/or processing 145, a current load of the transformer 5 can optionally be detected and a warning can be issued immediately if the safe rated power of the transformer 5 is detected to be exceeded.

[0095] The foregoing explanation of the embodiments describes the present invention exclusively in the context of examples. Of course, individual features of the embodiments may be freely combined with one another, provided that this is technically expedient, without departing from the scope of the present invention.

LIST OF REFERENCE SIGNS

[0096] 5 Transformer [0097] 20 Monitoring component [0098] 21 Receiving component [0099] 22 Evaluation component [0100] 23 Output component [0101] 25 Other sensors [0102] 26 Data processing section [0103] 27 Communication section [0104] 28 Time component, clock system [0105] 70 Network [0106] 80 Processing system [0107] 110 Receive [0108] 120 Frequency evaluation, Fourier transform [0109] 130 Output [0110] 140 Evaluation [0111] 145 Processing [0112] 210 Signal, low frequency signal [0113] 230 Evaluation means/elements [0114] 240 Monitoring information [0115] 245 Time information [0116] 250 Frequency components, spectrum