CN117148049B - Direct current arc discharge fault detection system, method and photovoltaic grid-connected system - Google Patents
Direct current arc discharge fault detection system, method and photovoltaic grid-connected system Download PDFInfo
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Abstract
The application discloses a direct current arc discharge fault detection system, a direct current arc discharge fault detection method and a photovoltaic grid-connected system; the method comprises the following steps: segment collection is carried out on the direct current, and a proportionality coefficient for signal correction is calculated according to the obtained direct current value; and then amplifying or reducing and correcting the corresponding high-frequency alternating current signal according to the size of the direct current through the corresponding proportionality coefficient, and bringing the corrected high-frequency alternating current signal into a direct current arc discharge detection algorithm to judge the arc discharge condition. The method is applied to a detection system; and the photovoltaic grid-connected system comprises the detection system. The beneficial effects of this application: compared with the traditional scheme, the method and the device can select different proportion coefficients to correct the current according to the current, so that the false alarm problem caused by current change can be effectively reduced, and the cost on hardware is not required to be increased, so that the method and the device are economical and practical.
Description
Technical Field
The application relates to the technical field of electrical faults, in particular to a direct current arc discharge fault detection method and a photovoltaic grid-connected system.
Background
Direct current arc discharge faults in a photovoltaic grid-connected system are a type of dangerous faults, and are susceptible to environmental conditions due to the presence of long-term exposed cables in the photovoltaic grid-connected system, especially when photovoltaic cables, connectors and conductors degrade in an aged photovoltaic device, the over-current protection device may fail to detect arc faults, resulting in unstable performance, electric shock and fire of flammable materials within or around the photovoltaic grid-connected system. In addition, the direct current arc discharge fault event in the photovoltaic grid-connected system is more and more common, and the system stability and the safety are seriously affected, so that continuous detection of the current of the photovoltaic grid-connected system is required when the photovoltaic grid-connected system works.
In general, the dc arc fault detection algorithm in the prior art relies on detection and analysis of current signals to a great extent, and a certain algorithm is generally used to analyze the change of the current signals during arc faults to serve as a basis for judging the arc faults. However, in actual operation of the photovoltaic grid-connected inverter, corresponding current signals under different working conditions are different. When the current signal corresponding to the photovoltaic panel under the condition of strong illumination is strong, the detection system can be mistakenly considered as an arc discharge fault working condition when relatively tiny change occurs; and when the light is weaker, the arcing signal is weaker, and when an arcing fault occurs, the detecting system may not report the arcing.
Disclosure of Invention
One of the objectives of the present application is to provide a method for detecting a dc arc discharge fault, which can solve at least one of the above-mentioned drawbacks of the related art.
Another object of the present application is to provide a dc arc fault detection system that can solve at least one of the above-mentioned drawbacks of the related art.
It is a further object of the present application to provide a photovoltaic grid-connected system that addresses at least one of the above-mentioned drawbacks of the prior art.
In order to achieve at least one of the above objects, the technical scheme adopted in the application is as follows: a direct current arc discharge fault detection method comprises the following detection steps:
s100: segment sampling is carried out on the direct current and the corresponding high-frequency alternating current signals;
s200: calculating a scaling factor for signal correction according to the obtained direct current value;
s300: amplifying or reducing and correcting the corresponding high-frequency alternating current signal according to the direct current value through a scaling factor;
s400: and carrying the corrected high-frequency alternating current signal into a direct current arc discharge detection algorithm to judge whether arc discharge occurs.
Step S200 includes the steps of:
s210: defining the maximum value of the collected direct current segment and the minimum current value of arc discharge required by the standard;
s220: selecting current sections close to two sides in a defined range as boundary current sections;
s230: arc discharge experiments with different current working conditions and different proportion coefficients are carried out on the boundary current section, and the optimal proportion coefficient is recorded and made into an array table;
in step S300, the corresponding scaling factor is directly selected from the array table according to the magnitude of the dc value.
Preferably, in step S220, the lengths of the boundary current segments located at both sides of the defined range are equal.
Preferably, in step S400, the dc arc discharge detection algorithm employs a neural network algorithm based on FFT analysis.
Preferably, the current segments within the defined range between the boundary current segments are intermediate current segments; the intermediate current section is used for parameter adjustment and training of a direct current arc discharge detection algorithm.
Preferably, the length of the intermediate current segment is 50% -80% of the length of the defined range.
The direct current arc discharge fault detection system comprises an acquisition control module and an AFCI detection module which are connected with each other; the acquisition control module is suitable for acquiring direct current and corresponding high-frequency alternating current signals and calculating a proportionality coefficient according to the acquired data; the AFCI detection module is suitable for receiving the data of the acquisition control module to correct the high-frequency alternating current signal and judge the arc discharge fault, and sending a control signal to the acquisition control module according to the judging result of the arc discharge fault, so that the acquisition control module is suitable for controlling the circuit system to perform corresponding actions.
Preferably, the acquisition control module comprises an acquisition unit and a control unit; the acquisition unit is suitable for acquiring a current high-frequency signal and sending the current high-frequency signal to the AFCI detection module; the control unit is suitable for collecting direct current, calculating a proportion coefficient, then sending the proportion coefficient to the AFCI detection module, and receiving a control signal of the AFCI detection module to control a circuit system to perform corresponding actions.
Preferably, the acquisition unit is a current transformer.
A photovoltaic grid-connected system comprises the direct current arc discharge fault detection system.
Compared with the prior art, the beneficial effect of this application lies in:
compared with the traditional scheme, the method and the device can select different proportion coefficients to correct the current according to the current, so that the false alarm problem caused by current change can be effectively reduced, and the cost on hardware is not required to be increased, so that the method and the device are economical and practical.
Drawings
FIG. 1 is a schematic diagram of the operation of the detection system according to the present invention.
FIG. 2 is a schematic diagram showing the distribution of the intermediate current segment and the boundary current segment within the current range defined in the present invention.
Fig. 3 is a schematic circuit structure of the photovoltaic grid-connected system in the invention.
Fig. 4 is a schematic diagram of a waveform corresponding to a small current arc discharge in the prior art.
Fig. 5 is a schematic diagram of the waveform corresponding to the small current arc discharge of the present invention.
Fig. 6 is a schematic diagram of a waveform corresponding to a large current arc discharge in the prior art.
Fig. 7 is a schematic diagram of the waveform corresponding to the large current arc discharge of the present invention.
In the figure: the photovoltaic module 100, the acquisition unit 200, the AFCI detection module 300, the control unit 400 and the inverter 500.
Detailed Description
The present application will be further described with reference to the specific embodiments, and it should be noted that, on the premise of no conflict, new embodiments may be formed by any combination of the embodiments or technical features described below.
In the description of the present application, it should be noted that, for the azimuth terms such as terms "center", "lateral", "longitudinal", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., the azimuth and positional relationships are based on the azimuth or positional relationships shown in the drawings, it is merely for convenience of describing the present application and simplifying the description, and it is not to be construed as limiting the specific protection scope of the present application that the device or element referred to must have a specific azimuth configuration and operation, as indicated or implied.
It should be noted that the terms "first," "second," and the like in the description and in the claims of the present application are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
One aspect of the present application provides a method for detecting a dc arc discharge fault, as shown in fig. 1, where a preferred embodiment includes the following detection steps:
s100: and (5) segment sampling is carried out on the direct current and the corresponding high-frequency alternating current signal.
S200: and calculating a scaling factor for signal correction according to the obtained direct current value.
S300: amplifying or reducing and correcting the corresponding high-frequency alternating current signal according to the direct current value through a scaling factor; that is, the high-frequency ac signal having a small dc value is amplified by the scaling factor, and the high-frequency ac signal having a large dc value is reduced by the scaling factor.
S400: and carrying the corrected high-frequency alternating current signal into a direct current arc discharge detection algorithm to judge whether arc discharge occurs.
It should be appreciated that the significance of its arcing is different for different current conditions. For small current, an arc with unobvious characteristics exists in the arc drawing process; for large currents, an arc with very obvious characteristics exists in the arc drawing process. In fact, if the same set of debugged or learned parameters are used for arc starting judgment for different current conditions, even if the set of parameters are optimal parameters, the parameters are still compromise values of arc with insignificant features and very significant features, so that no arc false alarm occurs for small current and no arc false alarm occurs for large current.
Therefore, in order to avoid or improve the arc failure reporting of small current and the arc failure reporting of large current in the prior art, the current signal adopted can be corrected before arc discharge judgment, namely, the adopted current signal is corrected appropriately through a proportion coefficient. Therefore, when the sampling value of the current signal is smaller, the sampling value can be properly amplified by multiplying the sampling value of the current signal by a proportional coefficient larger than 1, so that the judgment of arc striking failure caused by unobvious characteristics of the arc striking signal under the small current is avoided or reduced. When the current signal is strong, the sampling value can be properly reduced by multiplying the sampling value of the current signal by the proportionality coefficient smaller than 1, so that the judgment that no arcing is caused but the arcing is wrongly reported due to the tiny fluctuation under the large current is avoided or reduced.
More generally, the scheme of the application is to correct the sampling value of the current signal through the proportionality coefficient so that a smaller current value is increased through the proportionality coefficient and a larger current value is reduced through the proportionality coefficient. Therefore, the correction value of the smaller current and the correction value of the larger current can be positioned near the compromise value of the arc with the unobvious characteristic and the quite obvious characteristic of the traditional method, and the judgment accuracy of the arc discharge fault can be effectively improved.
It can be understood that, at present, the detection of the dc arc fault generally performs feature statistics and detection on the high-frequency signal of the dc current by a current detection mode. Therefore, when detecting the arc discharge fault of the direct current, not only the value of the direct current but also the high-frequency signal value corresponding to the direct current need to be collected. Meanwhile, the proportionality coefficient is related to the self-size of the direct current, so that the calculation of the proportionality coefficient can be directly obtained by calculating the value of the direct current.
For ease of understanding, the following may compare the schemes of the present application with the prior art by way of experimental simulation. The results of the comparison are shown in fig. 4 to 7. The blue waveform is a high-frequency alternating current signal corresponding to the direct current; the green waveform is the response of the program to arcing, and a high level indicates that the program detected arcing.
Fig. 4 is a schematic diagram of a waveform structure of a prior art arc discharge fault determination for small currents. As can be seen from fig. 4, there are obvious and many arcing faults in the blue waveform, but the arcing fault judgment cannot be triggered by the program to perform the arcing of the micro deformation due to the weak small current signal.
Fig. 5 is a schematic diagram of a waveform structure of the arcing judgment of the small current by the program after the method of the present application is adopted. As can be seen from fig. 5, there are significant and many arcing faults in the blue waveform, and the program is able to respond to trigger quickly and sensitively to arcing faults.
Fig. 6 is a schematic diagram of a waveform structure for judging a large-current arc discharge fault in the prior art. As can be seen from fig. 6, there is no obvious arcing fault in the blue waveform, but the program triggered the response of the arcing fault to the small deformation of the large current due to the large current signal.
Fig. 7 is a schematic diagram of waveform structure of the procedure for judging the arcing fault of the heavy current after the method of the present application is adopted. As can be seen from fig. 7, there is no significant arcing fault in the blue waveform, and the program also does not trigger an arcing fault response.
In summary, from the comparison results of fig. 4 to fig. 7, after the scheme of the present application is adopted, the program has good response speed and sensitivity to the dc arc discharge fault under the limit working condition compared with the prior art.
In this embodiment, as shown in fig. 2, the calculation of the scaling factor in step S200 includes the following steps:
s210: and defining the maximum value of the collected direct current segment and the minimum current value of the arc discharge required by the standard.
S220: and selecting the current sections close to two sides in the defined range as boundary current sections.
S230: arc discharge experiments with different current working conditions and different proportion coefficients are carried out on the boundary current section, and the optimal proportion coefficient is recorded and made into an array table.
It can be understood that the maximum value of the collected direct current fragments is taken as the upper limit of the defined range, and the minimum current value of arc discharge required by the standard is taken as the lower limit of the defined range; the current values of the possible dc-drawn arc in the dc-current segments that can be collected are generally within the above-mentioned defined range. The boundary current segment then belongs to two more extreme positions of the entire defined range, namely a position with a larger current value and a position with a smaller current value. The optimal proportional coefficient corresponding to the boundary current section can be obtained by carrying out direct current arc discharge judgment experiments under different current working conditions and different proportional coefficients on the two boundary current sections, and the optimal proportional coefficient required by correcting the smaller current value and the larger current value in the daily detection process is obtained.
For arc discharge experiments, specific experimental procedures are well known to those skilled in the art; the procedure of arc discharge implementation may be briefly described for ease of understanding. First, the working conditions of the current are classified, and different working conditions of the current can be obtained. Then, different proportional coefficients are given to the current signal to be detected based on a single current working condition, and multiple arc discharge judgment is carried out on the current signal corrected by the different proportional coefficients; and recording the proportionality coefficient comprehensively obtaining the optimal arcing judgment result by taking the false report as far as possible as a reference. And finally, arc discharge judgment of different proportion coefficients is carried out on the circuit signals to be detected under each current working condition, so that the optimal proportion coefficients corresponding to the different current working conditions can be obtained. The required array table can be obtained by recording the optimal proportionality coefficient; the Y axis of the array table is a direct current value, and the X axis of the array table is a corresponding proportional coefficient. Therefore, in the subsequent step S300, the corresponding scaling factor can be directly selected from the array table for correction only according to the magnitude of the dc current value.
It can be further understood that when the current value of the collected dc current segment is located between two boundary current segments within the defined range, the current value within the range is moderate, and the result of arc discharge judgment basically meets the requirement, so that the current value within the range can not be increased or reduced, i.e. the proportionality coefficient is 1.
In this embodiment, as shown in fig. 2, in step S220, the lengths of the boundary current segments located at both sides of the defined range are equal.
It will be appreciated that the length of the boundary current segment generally depends on how good the arcing condition is. Taking a boundary current segment near the lower limit of the defined range as an example, the lower limit of the boundary current segment is the lower limit of the defined range, and then the current is increased from the lower limit of the defined range to the current value corresponding to the arc discharge judgment without false alarm is the upper limit of the boundary current segment.
In general, the lengths of the two boundary current segments need to be determined through multiple experiments, and there may be a certain difference in length between the lengths of the two boundary current segments. However, in order to reduce the calculation amount of the algorithm, the lengths of the two boundary current segments may be set equal to each other when the boundary current segments are defined, and the specific length is based on the maximum value of the experimental lengths of the two boundary current segments.
In this embodiment, the dc arc discharge detection algorithm for performing dc arc discharge fault detection in step S400 is various, and the most common is a neural network algorithm based on FFT (fast fourier transform) analysis.
It should be appreciated that the specific process of the neural network algorithm is well known to those skilled in the art and will not be described in detail herein. But the core of determining the accuracy of the neural network algorithm is whether the training of the neural network algorithm is accurate. When the prior art adopts a neural network algorithm to perform fault detection of direct current arc discharge, a current segment corresponding to the fact that the arc characteristics are not obvious to the fact that the arc characteristics are very obvious is generally taken as a parameter to be trained in the algorithm. However, when training the neural network algorithm, the accuracy of the algorithm in judging the arc-striking fault cannot be improved, and even the accuracy of the algorithm in judging the arc-striking fault is reduced.
In order to improve the accuracy of the neural network algorithm in judging the direct current arc discharge fault, in this embodiment, a current segment located between boundary current segments within a defined range may be set as an intermediate current segment. When training the neural network algorithm, the adopted data corresponding to the intermediate current segment can be used for parameter adjustment and training of the direct current arc discharge detection algorithm.
It can be understood that the intermediate current segment has a moderate current value compared with the boundary current segment, and belongs to the optimal value for training the neural network algorithm. In addition, when the direct current data is sampled, the current value positioned in the boundary current section can be positioned at or near the middle current section through correction of the proportionality coefficient. Thus, the neural network algorithm will become meaningless for data of non-intermediate current segments (i.e., boundary current segments) as training inputs.
In this embodiment, as shown in FIG. 2, the length of the current segment with a defined range is L, and the length of the intermediate current segment is L 1 The length of the boundary current section is L 2 . Then there is l=l 1 +L 2 And L is 1 The value of/L is 0.5-0.8; i.e. the length of the intermediate current segment is 50% -80% of the length of the defined range.
It should be noted that, for the length of the intermediate current segment, if the value is too large, the end point value of the intermediate current segment is closer to the limit value of the defined range. Further, when the scaling factor of the intermediate current segment is 1, the arcing fault detection result may become undesirable for the use of the dc current having a value near the end point of the intermediate current segment. If the value is too small, the intermediate current segment may not be able to provide a sufficient range of data for the neural network algorithm to train. Meanwhile, the length of the boundary current segment is increased, so that the current segment which does not need to be corrected in the boundary current segment is possibly corrected, the calculated amount of an algorithm is increased, and the response speed of a program is reduced. Therefore, the length of the intermediate current segment needs to be within a reasonable range, and generally, the length of the intermediate current segment may be 50% -80% of the length of the defined range, and preferably may be 2/3 of the length of the defined range.
Another aspect of the present application provides a dc arc fault detection system, which may be used as a hardware carrier of the above dc arc fault detection method. As shown in fig. 3, one of the preferred embodiments includes an acquisition control module and an AFCI detection module 300 that are interconnected. The acquisition control module may acquire the dc current and the corresponding high-frequency ac signal, calculate a scaling factor according to the acquired data, and finally send the acquired current signal and the calculated scaling factor to the AFCI detection module 300 together. After receiving the data of the acquisition control module, the AFCI detection module 300 can correct the high-frequency ac signal by a corresponding proportionality coefficient, and judge the arc discharge fault according to the corrected high-frequency ac signal; and finally, sending a control signal to the acquisition control module according to the judgment result of the arc discharge fault, and further controlling the circuit system to perform corresponding actions by the acquisition control module.
In this embodiment, as shown in fig. 3, the acquisition control module includes an acquisition unit 200 and a control unit 400. The acquisition unit 200 may acquire a high frequency ac signal and transmit to the AFCI detection module 300. The control unit 400 may collect the dc current and calculate a scaling factor and send the scaling factor to the AFCI detection module 300; meanwhile, the control unit 400 may also receive a control signal sent by the AFCI detection module 300 to control the circuitry to perform a corresponding action.
It is understood that the specific structure and operation principles of the acquisition unit 200 and the control unit 400 are well known to those skilled in the art; the acquisition unit 200 is typically a Current Transformer (CT), and the control unit 400 is typically a control board.
It should be noted that the dc arc-striking fault detection system of the present application may be used in a circuit system with a dc arc-striking fault detection requirement, where the common circuit system includes a photovoltaic grid-connected system, a wind power generation system, a hydroelectric power generation system, and the like.
A further aspect of the present application provides a photovoltaic grid-connected system, as shown in fig. 1 to 3, wherein a preferred embodiment includes the dc arc fault detection system described above. The collection unit 200 may directly detect the output current of the photovoltaic module 100 and take the maximum value of the current that the photovoltaic module 100 can output as the upper limit of the defined range. The control unit 400 may be connected to the inverter 500, and thus the control unit 400 may collect the dc current input to the inverter 500 and calculate the corresponding scaling factor. Meanwhile, when the arc discharge fault occurs, the control unit 400 may drive the inverter 500 to perform the wave-sealing action according to the control signal of the AFCI detection module 300.
It should be appreciated that the output current intensity of the photovoltaic module 100 is affected by the illumination intensity; when the illumination is weak, the current value output by the photovoltaic module 100 is small; when the illumination is strong, the current value output by the photovoltaic module 100 is large. Therefore, two extreme conditions exist in the current working condition of the photovoltaic grid-connected system, and after the direct current arc-discharge fault detection system and the corresponding method are adopted, the arc-discharge fault judgment accuracy of the current working condition of the photovoltaic grid-connected system near the extreme value can be ensured, and further the working stability and the safety of the photovoltaic grid-connected system can be effectively improved.
It should also be appreciated that, during the photovoltaic power generation process, the electrical energy output by the photovoltaic module 100 is direct current, and the direct current output by the photovoltaic module 100 is subject to environmental influences such as illumination, so that there is a certain fluctuation. The inverter 500 requires a stable dc input, so that the dc power output from the photovoltaic module 100 needs to be dc filtered before entering the inverter 500.
In the case of the inverter 500, the dc power output from the photovoltaic module 100 may be filtered by the ripple of the discharge arc. Therefore, in order to improve the accuracy of the dc arc fault detection of the photovoltaic grid-connected system by the dc arc fault detection system, the output current of the photovoltaic module 100 needs to be directly collected by the collection unit 200. For the calculation of the scaling factor, a stable current value is often required to perform relatively convenient and accurate calculation. Therefore, the control unit 400 is connected to the inverter 500, so that the direct current output by the photovoltaic module 100 can be collected by the control unit 400 for calculation of the scaling factor after the pre-dc filtering of the inverter 500 is completed.
The foregoing has outlined the basic principles, main features and advantages of the present application. It will be appreciated by persons skilled in the art that the present application is not limited to the embodiments described above, and that the embodiments and descriptions described herein are merely illustrative of the principles of the present application, and that various changes and modifications may be made therein without departing from the spirit and scope of the application, which is defined by the appended claims. The scope of protection of the present application is defined by the appended claims and equivalents thereof.
Claims (9)
1. The direct current arc discharge fault detection method is characterized by comprising the following steps of:
s100: segment sampling is carried out on the direct current and the corresponding high-frequency alternating current signals;
s200: calculating a scaling factor for signal correction according to the obtained direct current value;
s300: amplifying or reducing and correcting the corresponding high-frequency alternating current signal according to the direct current value through a scaling factor;
s400: carrying the corrected high-frequency alternating current signal into a direct current arc discharge detection algorithm to judge whether arc discharge occurs or not;
step S200 includes the steps of:
s210: defining the maximum value of the collected direct current segment and the minimum current value of arc discharge required by the standard;
s220: selecting current sections close to two sides in a defined range as boundary current sections;
s230: arc discharge experiments with different current working conditions and different proportion coefficients are carried out on the boundary current section, and experimental data are recorded and made into an array table;
in step S300, the corresponding scaling factor is directly selected from the array table according to the magnitude of the dc value.
2. The direct current arc discharge fault detection method of claim 1, wherein: in step S220, the lengths of the boundary current segments located at both sides of the defined range are equal.
3. The direct current arc discharge fault detection method according to claim 1 or 2, characterized in that: in step S400, the dc arc discharge detection algorithm employs a neural network algorithm based on FFT analysis.
4. The direct current arc discharge fault detection method as claimed in claim 3, wherein: the current segments positioned between the boundary current segments within the defined range are intermediate current segments; the intermediate current section is used for parameter adjustment and training of a direct current arc discharge detection algorithm.
5. The direct current arc discharge fault detection method of claim 4, wherein: the length of the intermediate current segment is 50% -80% of the length of the defined range.
6. A direct current arc discharge fault detection system, adopting the direct current arc discharge fault detection method according to any one of claims 1-5, characterized in that: the system comprises an acquisition control module and an AFCI detection module which are connected with each other; the acquisition control module is suitable for acquiring direct current and corresponding high-frequency alternating current signals and calculating a proportionality coefficient according to the acquired data; the AFCI detection module is suitable for receiving the data of the acquisition control module to correct the high-frequency alternating current signal and judge the arc discharge fault, and sending a control signal to the acquisition control module according to the judging result of the arc discharge fault, so that the acquisition control module is suitable for controlling the circuit system to perform corresponding actions.
7. The direct current arc discharge fault detection system of claim 6, wherein: the acquisition control module comprises an acquisition unit and a control unit; the acquisition unit is suitable for acquiring a current high-frequency signal and sending the current high-frequency signal to the AFCI detection module; the control unit is suitable for collecting direct current, calculating a proportion coefficient, then sending the proportion coefficient to the AFCI detection module, and receiving a control signal of the AFCI detection module to control a circuit system to perform corresponding actions.
8. The direct current arc discharge fault detection system of claim 7, wherein: the acquisition unit is a current transformer.
9. A photovoltaic grid-tie system, characterized by: comprising a direct current arc discharge fault detection system as claimed in any one of claims 6-8.
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