CN107340459A - A kind of DC Line Fault arc method for measuring and system - Google Patents
A kind of DC Line Fault arc method for measuring and system Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1272—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
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Abstract
The present invention relates to a kind of DC Line Fault arc method for measuring and system, this method to include：The DC voltage of photovoltaic cell output is acquired by setting sample frequency, obtains output voltage data；Time Domain Processing is carried out to the output voltage data, obtains the average voltage U in each detection cycleavg, voltage variances sigma, maximum peak difference Um；Compared with a upper detection cycle, in the difference △ U of the average voltageavgDuring more than first threshold, if the difference △ σ of the voltage variance are more than the difference △ U of Second Threshold or the maximum peak value differencemMore than the 3rd threshold value, then frequency domain processing is carried out to the output voltage data, calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum；Utilize the BP neural network and characteristic vector space of training in advance, it is determined whether have electric arc generation.The present invention solves the problems, such as that existing DC Line Fault arc-detection is inaccurate, False Rate is high, improves the security of photovoltaic generating system.
Description
Technical field
The present invention relates to a kind of arc-detection technical field, more particularly to a kind of DC Line Fault arc method for measuring and it is
System.
Background technology
Electric arc is a kind of gas discharge phenomenon, the break-make of electric hot plug and switch contacts all there may be electric arc, but
This kind of electric arc will not typically cause electric fault, and electric arc is divided into direct-current arc and alternating current arc by electric current, and arcing events are normal
Contain huge energy, the safety of surrounding devices and staff are constituted a threat to.
In recent years, with the extensive use of photovoltaic generating system, especially photovoltaic battery panel is in building roof and exterior wall
Large-scale application, and the installation of most of photovoltaic arrays, what is utilized is all long string of high-voltage dc power supply, which increase with
The relevant safety problem of electric arc.Because influence of the fault electric arc to photovoltaic cell output characteristic is smaller, traditional over-voltage and over-current breaks
The generation of road device and thermal circuit beraker to prevention system fault electric arc is helpless, the electricity and photovoltaic generating system once breaks down
Arc, these electric arcs can make device powered, cause mounting system also powered, may make anyone electric shock of contact device, threaten
The life security of staff, in addition, lasting direct-current arc will produce high temperature, and then trigger fire, if do not take has in time
The safeguard procedures of effect, electrical equipment will be caused to damage, or a wide range of property damage.In recent years the ground such as America and Europe occur successively it is a lot of by
The fire that fault electric arc triggers, the lives and properties to people bring different degrees of loss.U.S.'s electrician's regulation (NEC) rule in 2011
The detection means and breaker of detection fault electric arc should be equipped with by determining photovoltaic generating system, and detection and isolation trigger device damage and fire
The DC Line Fault electric arc of calamity hidden danger solves the problems, such as into necessary.
Current such arc method for measuring is roughly divided into two kinds：First, the waveform such as voltage, electric current when occurring according to electric arc
Change judges arc fault.But the direct-current arc in photovoltaic generating system with the property of alternating current arc because be very different, first
First direct-current arc is a kind of random unstable signal, such a to be based on waveform without alternating current periodically " flat shoulder " portion's feature
Although detection method it is simple but applicability is low.Second, the variation characteristic of electric current time domain or frequency domain when being occurred by detecting electric arc
Judge that electric arc produces.Such method detection object is electric current, and applicability is wide, and the C-V characteristic of photo-voltaic power supply determines inverter just
Electric arc, electric current temporal signatures unobvious often occur during work, and are easily disturbed by other factors, False Rate is high.Meanwhile only to electric current
The detection method of frequency domain character due to criterion it is single there is also False Rate it is high the shortcomings that.
The content of the invention
The present invention provides a kind of DC Line Fault arc method for measuring and system, solves existing photovoltaic generating system and produces direct current
Fault electric arc detection is inaccurate, is easily disturbed, the problem of False Rate is high, improves the security of photovoltaic generating system.
To realize object above, the present invention provides following technical scheme：
A kind of DC Line Fault arc method for measuring, including：
The DC voltage of photovoltaic cell output is acquired by setting sample frequency, obtains output voltage data；
Time Domain Processing is carried out to the output voltage data, obtains the average voltage U in each detection cycleavg, electricity
Press variances sigma, maximum peak difference Um；
Compared with a upper detection cycle, the difference △ U of average voltage are calculatedavg, voltage variance difference △
σ, maximum peak value difference difference △ Um；
In the difference △ U of the average voltageavgDuring more than first threshold, if the difference △ σ of the voltage variance are big
In Second Threshold or the difference △ U of the maximum peak value differencemMore than the 3rd threshold value, then frequency domain is carried out to the output voltage data
Processing, calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum；
BP neural network and the characteristic vector space using training in advance, it is determined whether have electric arc generation
Preferably, frequency domain processing is carried out to the output voltage data, calculate each frequency range harmonic energy and, and form
The characteristic vector space of harmonic energy sum, including：
Fourier transform is carried out to the DC voltage data of N number of collection point, obtains voltage spectrum；
According to nyquist frequency, respectively N number of frequency range, the harmonic energy and W of each frequency range are calculated；
By the harmonic energy and constitutive characteristic vector space [W of N number of frequency range1、W2、W3、……WN]。
Preferably,
Methods described also includes：The BP neural network is trained in such a way：
Determine the topological structure of the BP neural network；
Photovoltaic generating system is gathered respectively under the conditions of unexpected startup, load changing, different illumination, different DC voltages
Voltage data, form first kind learning sample；
The first kind learning sample is input in the BP neural network and carries out repetition training, test, until possessing
Identification is without ability caused by electric arc；
Photovoltaic generating system electric arc different under the conditions of different DC voltages is gathered respectively, and position generation electric arc occurs
Voltage data, form the second class learning sample；
The second class learning sample is input in the BP neural network and carries out repetition training, test, until possessing
Identify that electric arc produces ability.
Preferably, in addition to：If the difference △ U of the average voltageavgLess than first threshold, it is determined that be without electricity
Arc produces.
Preferably, in addition to：In the difference △ U of the average voltageavgDuring more than first threshold, if the voltage
When the difference △ σ of variance are less than Second Threshold, it is determined that be to be produced without electric arc.
Preferably, in addition to：In the difference △ U of the average voltageavgDuring more than first threshold, if the maximum
The difference △ U of peak differencemDuring less than three threshold values, it is determined that be to be produced without electric arc.
Preferably, in addition to：When there is electric arc generation, arc fault alarm signal is sent.
The present invention also provides a kind of DC Line Fault arc detection system, including：Data acquisition unit, data processing unit and
Recognition unit；
The data acquisition unit is used to be acquired the DC voltage of photovoltaic cell output by setting sample frequency, obtains
To output voltage data, and it is sent to the data processing unit；
The data processing unit is used to carry out Time Domain Processing to the output voltage data, obtains each detection cycle
Interior average voltage Uavg, voltage variances sigma, maximum peak difference Um, and compared with a upper detection cycle, be calculated
The difference △ U of average voltageavg, voltage variance difference △ σ, the difference △ U of maximum peak value differencem；In the average voltage
Difference △ UavgIt is more than Second Threshold or the maximum peak value difference more than the difference △ σ of first threshold and the voltage variance
Difference △ UmDuring more than three threshold values, frequency domain processing is carried out to the output voltage data, calculates the harmonic wave energy of each frequency range
Amount and, and form the characteristic vector space of harmonic energy sum；
The recognition unit is used to determine whether using the BP neural network and the characteristic vector space of training in advance
Electric arc produces.
Preferably, in addition to：Alarm unit；When there is electric arc generation, the recognition unit triggers the alarm unit and entered
Row alarm.
Preferably, the alarm unit is alarmed by the way of arc fault alarm signal is sent.
The present invention provides a kind of DC Line Fault arc method for measuring and system, passes through the voltage that is exported to photovoltaic cell group
The change of temporal signatures and frequency domain character detects DC Line Fault electric arc, solves existing photovoltaic generating system and produces DC Line Fault electricity
Arc detection is inaccurate, is easily disturbed, the problem of False Rate is high, improves the security of photovoltaic generating system.
Brief description of the drawings
In order to illustrate more clearly of the specific embodiment of the present invention, the required accompanying drawing used in embodiment will be made below
Simply introduce.
Fig. 1：It is a kind of schematic diagram of DC Line Fault arc method for measuring provided by the invention.
Embodiment
In order that those skilled in the art more fully understand the scheme of the embodiment of the present invention, below in conjunction with the accompanying drawings and implement
Mode is described in further detail to the embodiment of the present invention.
Easily disturbed for the DC Line Fault arc-detection presence currently to photovoltaic generating system by external factor, False Rate height
The problem of, the present invention provides a kind of DC Line Fault arc method for measuring and system, passes through the voltage that is exported to photovoltaic cell group
The change of temporal signatures and frequency domain character detects DC Line Fault electric arc, solves existing photovoltaic generating system and produces DC Line Fault electricity
Arc detection is inaccurate, is easily disturbed, the problem of False Rate is high.
As shown in figure 1, it is a kind of schematic diagram of DC Line Fault arc method for measuring provided by the invention.This method include with
Lower step：
S1：The DC voltage of photovoltaic cell output is acquired by setting sample frequency, obtains output voltage data；
S2：Time Domain Processing is carried out to the output voltage data, obtains the average voltage in each detection cycle
Uavg, voltage variances sigma, maximum peak difference Um；
S3：Compared with a upper detection cycle, the difference △ U of average voltage are calculatedavg, voltage variance difference
Value △ σ, maximum peak value difference difference △ Um；
S4：In the difference △ U of the average voltageavgDuring more than first threshold, if the difference △ of the voltage variance
σ is more than the difference △ U of Second Threshold or the maximum peak value differencemMore than the 3rd threshold value, then the output voltage data are carried out
Frequency domain processing, calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum；
S5：BP neural network and the characteristic vector space using training in advance, it is determined whether have electric arc generation.
Specifically, can be carried out for DC Line Fault arc-detection using intelligent junction box, with certain sample frequency fs
Gather the DC voltage data signal in photovoltaic generating system.The header box can be that photovoltaic group string header box or photovoltaic arrays conflux
Equipment.If the DC voltage data points of collection are N, the arc-detection cycle isEnter to collecting voltage digital signal
The processing of row time domain data, mainly calculate the average voltage U of N number of gathered dataavg, voltage variances sigma, maximum peak difference Um。
When electric arc occurs, because the presence of arc voltage makes average voltage to become big suddenly or diminish, and voltage variance after electric arc occurs
All become big with the peak difference of maximum, to avoid the factors such as shadow occlusion or illumination from causing average voltage value mutation to bring erroneous judgement,
In the preliminary judgement for whether producing electric arc, first using average voltage value mutation as the first decision condition, voltage variance and maximum
Peak difference mutation as further decision condition.
In actual applications, mainly it is defined for the setting of first threshold, Second Threshold and the 3rd threshold value by being actually needed, can
First threshold is set to 15, Second Threshold is set to 0.2, and the 3rd threshold value is set to 6.Meanwhile the BP neural network by having trained, will
The input sample that the characteristic vector space is known as the BP neural network, it is identified to whetheing there is electric arc generation, if institute
It is 1 to state BP neural network output result, is defined as having electric arc generation, otherwise, it determines to be produced without electric arc.
It should be noted that maximum peak value difference referred within the sampling period, the maximum voltage of photovoltaic generating system output voltage
With the difference of minimum voltage.
Further, to the output voltage data carry out frequency domain data processing, calculate each frequency range harmonic energy and, and
The characteristic vector space of harmonic energy sum is formed, including：
Step 1：Fourier transform is carried out to the DC voltage data of N number of collection point, obtains voltage spectrum；
Step 2：According to nyquist frequency, respectively N number of frequency range, the harmonic energy and W of each frequency range are calculated；
Step 3：By the harmonic energy and constitutive characteristic vector space [W of N number of frequency range1、W2、W3、……WN]。
Specifically, because in different voltage class electric arc occurs for photovoltaic cell, voltage frequency domain different frequency range can be caused humorous
Ripple content is changed, and spectrum signature is different from.In order to ensure it is various in the case of can extract frequency domain character, again reduce load
High-frequency power electronic switchs the influence to frequency domain character, need to carry out Fourier transform to the voltage data collected, obtain voltage
Frequency spectrum.To reduce influence of the load electric electronic switch harmonic wave to spectrum analysis, by obtained voltage spectrum in Nyquist frequency
Rate, i.e.,In the range of reject switching frequency point and its order harmonic frequencies point after, N number of frequency is divided into by low frequency to high frequency
Section.Harmonic energy sum in each frequency range of voltage spectrum is calculated as：Wi=∑s | A (fi)|2, wherein, i=1,2,3 ... ..N, | A
(fi) | represent in Frequency point fiLocate harmonic component amplitude.
Further, methods described also includes：The BP neural network is trained in such a way：
Step 4：Determine the topological structure of the BP neural network；
Step 5：Photovoltaic generating system is gathered respectively in unexpected startup, load changing, different illumination, different direct current press strips
Voltage data under part, form first kind learning sample；
Step 6：The first kind learning sample is input in the BP neural network and carries out repetition training, test, directly
Identified to possessing without ability caused by electric arc；
Step 7：Photovoltaic generating system electric arc different under the conditions of different DC voltages is gathered respectively, and position occurs
The voltage data of electric arc, form the second class learning sample；
Step 8：The second class learning sample is input in the BP neural network and carries out repetition training, test, directly
Ability is produced to possessing identification electric arc.
In actual applications, for BP neural network topological structure, using universal architecture, including：Input layer, hidden layer and
Output layer.BP neural network is by sample training and the detection algorithm with electric arc and non-electric arc recognition capability tested.Through
Cross and train the BP neural network to possess automatic classification and identification electric arc and the recognition capability without conditions at the arc, can know as online
Whether there is not electric arc generation.
Further, this method also includes：If the difference △ U of the average voltageavgDuring less than first threshold, then really
It is set to no electric arc to produce.In the difference △ U of the average voltageavgDuring more than first threshold, if the difference of the voltage variance
When value △ σ are less than Second Threshold, it is determined that be to be produced without electric arc.In the difference △ U of the average voltageavgMore than the first threshold
During value, if the difference △ U of the maximum peak value differencemDuring less than three threshold values, it is determined that be to be produced without electric arc.
Further, this method also includes：When there is electric arc generation, arc fault alarm signal is sent.
It can be seen that the present invention provides a kind of DC Line Fault arc method for measuring, pass through the voltage that is exported to photovoltaic cell group
The change of temporal signatures and frequency domain character detects DC Line Fault electric arc, solves existing photovoltaic generating system and produces DC Line Fault electricity
Arc detection is inaccurate, is easily disturbed, the problem of False Rate is high, improves the security of photovoltaic generating system.
The present invention also provides a kind of DC Line Fault arc detection system, and the system includes：Data acquisition unit, data processing
Unit and recognition unit.The data acquisition unit is used to carry out the DC voltage of photovoltaic cell output by setting sample frequency
Collection, obtains output voltage data, and send the data processing unit.The data processing unit is used for the output electricity
Press data to carry out Time Domain Processing, obtain the average voltage U in each detection cycleavg, voltage variances sigma, maximum peak difference
Um, and compared with a upper detection cycle, the difference △ U of average voltage are calculatedavg, voltage variance difference △ σ,
The difference △ U of maximum peak value differencem；In the difference △ U of the average voltageavgMore than first threshold and the voltage variance
Difference △ σ be more than the difference △ U of Second Threshold or the maximum peak value differencemDuring more than three threshold values, to the output voltage
Data carry out frequency domain processing, calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum；
The recognition unit is used to determine whether using the BP neural network and the characteristic vector space of training in advance
Electric arc produces
Further, the system also includes：Alarm unit；When there is electric arc generation, the recognition unit triggers the alarm
Unit is alarmed.
Further, member is alarmed by the way of arc fault alarm signal is sent during the alarm power transmission.
In actual applications, data acquisition unit and data processing unit and identification module are all often integrated in intelligent junction
In case, wherein data processing unit can use single-chip microcomputer or MCU, and identification module is frequently with the chip reality with neural computing
It is existing.The data collecting card that can use NI companies for data acquisition unit is realized.
It can be seen that the present invention provides a kind of DC Line Fault arc detection system, by with BP neural network identification function
Identification module detects DC Line Fault electric arc, and solving existing photovoltaic generating system, to produce DC Line Fault arc-detection inaccurate, easily
It is disturbed, the problem of False Rate is high, improves the security of photovoltaic generating system.
Construction, feature and the action effect of the present invention, above institute is described in detail according to diagrammatically shown embodiment above
Only presently preferred embodiments of the present invention is stated, but the present invention is not to limit practical range shown in drawing, it is every according to structure of the invention
Want made change, or be revised as the equivalent embodiment of equivalent variations, when still without departing from specification and illustrating covered spirit,
All should be within the scope of the present invention.
Claims (10)
- A kind of 1. DC Line Fault arc method for measuring, it is characterised in that including：The DC voltage of photovoltaic cell output is acquired by setting sample frequency, obtains output voltage data；Time Domain Processing is carried out to the output voltage data, obtains the average voltage U in each detection cycleavg, voltage side Poor σ, maximum peak difference Um；Compared with a upper detection cycle, the difference △ U of average voltage are calculatedavg, voltage variance difference △ σ, most The difference △ U of big peak differencem；In the difference △ U of the average voltageavgDuring more than first threshold, if the difference △ σ of the voltage variance are more than the The difference △ U of two threshold values or the maximum peak value differencemMore than the 3rd threshold value, then the output voltage data are carried out at frequency domain Reason, calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum；BP neural network and the characteristic vector space using training in advance, it is determined whether have electric arc generation.
- 2. detection method according to claim 1, it is characterised in that frequency domain processing is carried out to the output voltage data, Calculate each frequency range harmonic energy and, and form the characteristic vector space of harmonic energy sum, including：Fourier transform is carried out to the DC voltage data of N number of collection point, obtains voltage spectrum；According to nyquist frequency, respectively N number of frequency range, the harmonic energy and W of each frequency range are calculated；By the harmonic energy and constitutive characteristic vector space [W of N number of frequency range1、W2、W3、……WN]。
- 3. detection method according to claim 1, it is characterised in that methods described also includes：Train in such a way The BP neural network：Determine the topological structure of the BP neural network；Voltage of the photovoltaic generating system under the conditions of unexpected startup, load changing, different illumination, different DC voltages is gathered respectively Data, form first kind learning sample；The first kind learning sample is input in the BP neural network and carries out repetition training, test, until possessing identification Without ability caused by electric arc；Photovoltaic generating system electric arc different under the conditions of different DC voltages is gathered respectively, and the voltage that electric arc occurs for position occurs Data, form the second class learning sample；The second class learning sample is input in the BP neural network and carries out repetition training, test, until possessing identification Electric arc produces ability.
- 4. detection method according to claim 1, it is characterised in that also include：If the difference of the average voltage △UavgLess than first threshold, it is determined that be to be produced without electric arc.
- 5. detection method according to claim 1, it is characterised in that also include：In the difference △ of the average voltage UavgDuring more than first threshold, if the difference △ σ of the voltage variance are less than Second Threshold, it is determined that be to be produced without electric arc.
- 6. detection method according to claim 1, it is characterised in that also include：In the difference △ of the average voltage UavgDuring more than first threshold, if the difference △ U of the maximum peak value differencemDuring less than three threshold values, it is determined that be to be produced without electric arc It is raw.
- 7. according to the detection method described in any one of claim 1 to 6, it is characterised in that also include：When there is electric arc generation, Send arc fault alarm signal.
- A kind of 8. DC Line Fault arc detection system, it is characterised in that including：Data acquisition unit, data processing unit and knowledge Other unit；The data acquisition unit is used to be acquired the DC voltage of photovoltaic cell output by setting sample frequency, obtains defeated Go out voltage data, and be sent to the data processing unit；The data processing unit is used to carry out Time Domain Processing to the output voltage data, obtains in each detection cycle Average voltage Uavg, voltage variances sigma, maximum peak difference Um, and compared with a upper detection cycle, voltage is calculated The difference △ U of average valueavg, voltage variance difference △ σ, the difference △ U of maximum peak value differencem；In the difference of the average voltage Value △ UavgMore than the difference that the difference △ σ of first threshold and the voltage variance are more than Second Threshold or the maximum peak value difference Value △ UmDuring more than three threshold values, to the output voltage data carry out frequency domain processing, calculate each frequency range harmonic energy and, And form the characteristic vector space of harmonic energy sum；The recognition unit is used to determine whether electric arc using the BP neural network and the characteristic vector space of training in advance Produce.
- 9. detecting system according to claim 8, it is characterised in that also include：Alarm unit；When there is electric arc generation, The recognition unit triggers the alarm unit and alarmed.
- 10. detecting system according to claim 8, it is characterised in that the alarm unit is using transmission arc fault report The mode of alert signal is alarmed.
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| CN113049922A (en) * | 2020-04-22 | 2021-06-29 | 青岛鼎信通讯股份有限公司 | Fault arc signal detection method adopting convolutional neural network |
| CN113125913A (en) * | 2021-05-07 | 2021-07-16 | 珠海格力电器股份有限公司 | Arc fault detection method and device and direct-current electric appliance |
| CN113447773A (en) * | 2021-06-21 | 2021-09-28 | 东莞新能安科技有限公司 | Arc detection method and device and energy storage battery system |
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