CN115566999A - Photovoltaic array fault detection and positioning method based on time domain reflection method - Google Patents
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Abstract
The invention relates to the field of fault diagnosis of photovoltaic power generation systems, in particular to a photovoltaic array fault detection and positioning method based on a time domain reflection method, which comprises the following steps: injecting a step signal into the photovoltaic array; adjusting a sampling interval according to the scale of the array to be detected to obtain a reflection waveform in a normal state and a reflection waveform in a fault detection range; carrying out wavelet threshold denoising processing on the reflection signals of the fault array; calculating to obtain a signal amplitude; and judging whether the fault occurs according to a preset fault detection threshold value, and if the fault occurs, positioning a fault point according to a time delay estimation algorithm. According to the invention, fault detection is carried out according to the characteristic that the impedance value of the fault point changes when the photovoltaic array fails, the fault point is positioned by measuring the time difference between an incident signal and a reflected signal of the fault point, the fault diagnosis function can be realized by using an external detection device, the addition and the transformation of electrical equipment are not required for the photovoltaic power generation system, good fault point detection and positioning effects are achieved, the problem that each component is manually dismantled and detected one by one in the photovoltaic array fault detection process is avoided, the operation and maintenance efficiency of the photovoltaic power station is improved, and the safety of maintenance personnel is ensured.
Description
Technical Field
The invention relates to the field of fault diagnosis of photovoltaic power generation systems, in particular to a photovoltaic array fault detection and positioning method based on a time domain reflection method.
Background
In recent years, the accumulated loading capacity of photovoltaic power generation in China is increased year by year, and the accumulated grid-connected capacity reaches 300.2GW at the end of 3 months in 2022, wherein the accumulated photovoltaic power generation accounts for 63.6%. Meanwhile, the state development reform committee issues policies related to new energy internet surfing electricity prices, and new recorded photovoltaic projects are subjected to flat price internet surfing. Under the background that the proportion of photovoltaic power generation is steadily improved, the cost is rapidly reduced, and the photovoltaic power generation enters a low-price and non-subsidy development stage, the important problems of high labor cost proportion, low intelligent degree and the like in the photovoltaic industry are focused, the operation cost of the industry is further reduced, the high-quality development of the photovoltaic power generation industry is promoted, and the method is an important measure for realizing the targets of carbon peak reaching and carbon neutralization in China on schedule.
With the large-scale development of photovoltaic power generation and the down-regulation of photovoltaic subsidies, the importance of daily maintenance and fault diagnosis of photovoltaic power stations is increasingly prominent. Under the influence of a solar energy resource distribution rule and a land governance policy, a photovoltaic power generation system is often installed in regions with severe weather environments such as deserts, gobi and desert and is easily influenced by external environmental factors such as solar irradiance, temperature, humidity, dust, hail and the like in the operation process, various electrical faults caused by the reasons such as cell breakage, poor contact of a wiring terminal, cable damage and aging occur, the electrical faults comprise ground faults, line-to-line short-circuit faults, circuit breaking faults, arc faults and the like, the power generation efficiency can be reduced by the faults, more destructive consequences can be caused, such as component damage, fire disasters and the like, the power generation performance of the whole photovoltaic component series array is seriously reduced, and even the photovoltaic system cannot generate power, so that the photovoltaic system must be protected by corresponding fault detection and isolation technologies.
Photovoltaic arrays often avoid faults by installing overcurrent protection devices, ground fault detection circuit breakers, and the like. However, due to the specific working characteristics of the photovoltaic system, the protection devices cannot play their due roles, for example, under the condition of low irradiance, the current of a fault component is low, and the current protection device cannot detect the short-circuit fault between lines; ground fault detection circuit breakers may fail under low irradiance and high resistance faults; optimization of a Maximum Power Point Tracking (MPPT) technology to a power grid causes that a circuit breaker cannot judge circuit abnormality. In addition, the circuit structure of the photovoltaic array usually adopts an SP structure, and when the photovoltaic array fails, the devices can only locate the failed component series array, and the failure point cannot be accurately located. According to the relevant design standards of photovoltaic power station design specifications (GB 50797-2012), the maximum series number of photovoltaic modules of a photovoltaic power station can reach 25-30, and the photovoltaic power station is mostly installed in severe environments such as high mountains and deserts. Therefore, a quick and effective fault diagnosis and positioning technology is established, and the method has important significance for strengthening daily maintenance and fault diagnosis of the photovoltaic power station and promoting safe, stable and reliable operation of a photovoltaic power generation system.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a method for detecting and locating a fault of a photovoltaic array based on a time domain reflectometry, wherein the fault detection is performed according to a characteristic that an impedance value of a fault point of the photovoltaic array changes, and the method has a good effect on locating the fault in the photovoltaic array.
In order to achieve the purpose, the invention provides the following technical scheme:
a photovoltaic array fault detection and positioning method based on a time domain reflectometry method comprises the following steps:
Furthermore, the detection device comprises a signal generation device, a signal acquisition device and a T-shaped BNC three-way connector, wherein the anodes of the signal generation device and the signal acquisition device are respectively connected with any two interfaces in the T-shaped BNC three-way connector, and the cathodes of the signal acquisition device and the signal generation device are connected with a photovoltaic array ground wire or a photovoltaic array metal frame; and the positive electrode of the photovoltaic array is connected to the rest interface of the T-shaped BNC three-way connector. Preferably, the photovoltaic array is communicated with the T-shaped BNC tee by introducing a 'BNC-MC 4' adapter interface.
The connection process of the whole system needs to be closely matched, namely, the impedance of the cable is ensured to be continuous, the conductivity is good, meanwhile, the influence of the connector needs to be considered, and the phenomenon that the reflected signal cannot be obtained due to the fact that the impedance of the signal connector is unmatched to cause signal attenuation is avoided. In addition, the impedance matching between the signal generating device and the signal collecting device is ensured, and the generation of interference signals is reduced. In order to ensure the smooth operation of the test, the signal generating device, the signal collecting device, the T-shaped BNC three-way connector, the BNC-MC4 adapter and the photovoltaic module are tightly connected, and simultaneously, the signal generating device, the signal collecting device and the BNC three-way connector interface are matched with the impedance, namely, the input impedance and the output impedance are 50 ohms. Because the BNC is a coaxial line output interface and has two-way signal output of a positive pole and a negative pole, the MC4 interface is single-way output, and the BNC-MC4 adapter is realized by simple manufacture, namely, an outgoing line of a BNC male connector is divided into a positive pole wire and a negative pole wire, the positive pole wire is connected with a binding post of the MC4 adapter, and the negative pole wire is connected with a photovoltaic assembly ground wire so as to complete a signal loop.
Further, the signal generating device in step 1 adopts a square wave signal generator which generates step signals with rise time less than 10ns, voltage amplitude less than 5V and frequency less than 100 KHz.
Further, the signal sampling device in step 1 uses a signal sampling device with a sampling rate greater than 50 MSPS.
In order to complete the fault detection of the photovoltaic array, certain requirements are designed on a signal generator and a signal acquisition device. The time domain reflection method mainly uses singular points of signals to detect faults, namely, the fault detection can be realized only when the sudden change positions of the signals reach certain output frequency. By adopting the technical scheme, in order to achieve the output of high-frequency signals, the signal generator is provided with a square wave signal generator which is used for outputting low-voltage high-speed step signals with the rise time of less than 10ns, the voltage amplitude of less than 5V and the frequency of less than 100KHz as a signal generating device.
Meanwhile, in the process of collecting high-frequency signals, if the sampling rate and the resolution ratio are too low, fault signals cannot be effectively captured, and fault detection is affected, in actual use, the sampling rate of the signal collecting device should be larger than 50MSPS, and meanwhile, the signal collecting device should have a certain resolution ratio, so that small-scale faults such as cable breakage, connector loosening and the like can be clearly identified, therefore, the signal collecting device uses the signal collecting device with the sampling rate larger than 50MSPS, and the resolution ratio should reach more than 8 bits.
Further, the denoising processing in the step 4 includes the following steps:
step 41: performing multi-layer wavelet decomposition on the original signal by using DB4 wavelet basis, and extracting approximate coefficient vector A = [ a ] of each layer 1 ,a 2 ,a 3 ,……,a n ]Extracting detail coefficient vector D = [ D ] of each layer 1 ,d 2 ,d 3 ,……,d n ]；
Step 42: denoising the detail coefficients containing the noise signals, and removing at least the front 3 layers of detail coefficients;
step 43: wavelet reconstruction is carried out on the wavelet coefficient after denoising treatment, and an approximate coefficient a is utilized n And a detail coefficient d n And obtaining a denoised reflection signal waveform.
Further, the signal amplitude calculation method in step 6 includes: n is a radical of hydrogen sub,i ＝A si -A Ni In the formula A si And A Ni The amplitudes of the ith sampling point of the reflected signals of the fault-free system and the fault system are respectively.
Further, the preset fault detection threshold in step 7 is set to be 5% -10% of the voltage amplitude of the step signal, and when the signal amplitude obtained in step 6 is larger than the fault detection threshold, it is determined that a fault occurs.
Further, the fault distance in step 7 can be calculated by the following method:
(1) Obtaining the time when the signal rises rapidly as the incident time delay t 0 And obtaining the time when the reflected wave exceeds the threshold critical point as the reflection time delay t 1 And the propagation velocity v of the signal in the photovoltaic array;
(2) Calculating to obtain the signal time delay t of the signal passing through the photovoltaic array and reflected back, wherein t = t 1 -t 0 ；
(3) Calculating the fault distance L of the fault point, wherein the fault distance L is calculated by a time delay estimation algorithm to obtain:
further, the fault distance in step 7 can be calculated by the following method:
to facilitate detection, the art typically equates the distance to failure to the time delay t of a single photovoltaic module d Either side of
In the formula L d The signal propagation distance corresponding to a single component;
v is obtained through conversion, and is brought into a time delay estimation algorithm to obtain:
since the fault distance is positively correlated with the number of components, the positions of the available fault points are as follows:
where n is the position of the nth component in the photovoltaic array.
Therefore, the fault distance can be calculated by the following steps according to the principle:
(1) Calculating the total signal time delay t: obtaining the time when the signal rises rapidly as the incident time delay t 0 And obtaining the time when the reflected wave exceeds the threshold critical point as the reflection time delay t 1 And calculating the signal time delay t of the signal passing through the photovoltaic array and reflected back, wherein t = t 1 -t 0 ；
(2) Determining the time delay t corresponding to a single component d : selecting a standard photovoltaic module, injecting a step signal into the standard photovoltaic module, and measuring the corresponding time delay through calibration measurement, namely the time delay t corresponding to a single module d ；
(3) Calculating a fault distance n: calculating the fault distance n by the following formula so as to determine the position of the fault point,
the time domain reflection method mainly realizes fault location based on the directivity and reflectivity in the wave propagation process, and the accurate location of fault points is mainly realized by a method for analyzing output signals in a time domain.
In the application of a photovoltaic power generation system, various transmission lines and power transmission media are widely used as core components for energy transportation, including main and auxiliary grid lines for connecting photovoltaic cells, connecting cables between photovoltaic modules and the like. In the positioning technology based on the time domain reflection method, the basic method for realizing fault positioning and fault diagnosis is mainly based on the traveling wave transmission theory in the transmission line, and after the frequency of a transmission signal is improved, the transmission mode of the signal in the transmission line is not considered according to a common lead, but the transmission mode is considered to have distributed resistance, distributed inductance, distributed capacitance and distributed conductance effects. The high-frequency current flowing on the surface of the conductor can generate a skin effect, so that the effective conducting area of the conductor is reduced, and the high-frequency resistance is increased; the high-frequency current generates high-frequency magnetism around the lead; because of the voltage between the wires, a high-frequency electric field exists between the wires; in addition, because the dielectric around the wire is not ideal insulation, the phenomenon of electric leakage also exists, when the geometric length of the transmission line and the wavelength of the electromagnetic wave are in the same order of magnitude, the characteristics of phase lag, skin effect, phase shift caused by radiation effect, transmission impedance increase, signal attenuation and the like of the wave in the transmission process cannot be ignored, and the signal can change along with time and displacement in the transmission process, so that the method is used for detecting.
According to the traveling wave transmission theory, the waves on the transmission line are formed by superposing incident waves and reflected waves, and when impedance loads connected to two ends of the transmission line are matched with the characteristic impedance of the transmission line, the incident signals can be completely transmitted from one end to the other end without reflection and transmission phenomena. On the contrary, the traveling wave will generate the reflection and transmission phenomena when encountering the wave impedance mismatch points such as fault points, terminal joints and loads. The time domain reflection technology usually injects a low-voltage pulse signal into a photovoltaic system to be tested for fault diagnosis, and when the line wave impedance of any point in a transmission line is matched, an incident signal can be completely transmitted from one end to the other end, and the reflection or refraction phenomenon is avoided. On the contrary, when the traveling wave meets a wave impedance mismatching point such as a short circuit, an open circuit fault point, a terminal connector and a load, the reflection and transmission phenomena of the traveling wave can occur, so that the electric wave state of the transmission line at the corresponding moment can be described by measuring and calculating the change condition of the reflection coefficient of the signal in the transmission process, and the fault detection and positioning of the photovoltaic array can be realized.
Compared with the prior art, the photovoltaic array fault detection and positioning method has the following beneficial effects:
according to the invention, fault detection is carried out according to the characteristic that the impedance value of the fault point changes when the photovoltaic array fails, the fault point is positioned by measuring the time difference between an incident signal and a reflected signal of the fault point, the fault diagnosis function can be realized by using an external detection device, the addition and the transformation of electrical equipment are not required for the photovoltaic power generation system, good fault point detection and positioning effects are achieved, the problem that each component is manually dismantled and detected one by one in the photovoltaic array fault detection process is avoided, the operation and maintenance efficiency of the photovoltaic power station is improved, and the safety of maintenance personnel is ensured.
Drawings
FIG. 1 is a schematic flow chart of a fault detection and location method according to the present invention;
FIG. 2 is a block diagram of the connection of the detection device and the photovoltaic array required for fault detection and location according to the present invention;
FIG. 3 is a waveform diagram of an initial reflection of a reflection signal within a fault detection range obtained by the present invention;
FIG. 4 is a waveform diagram of a reflection signal processed by denoising according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the examples and the accompanying drawings. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Example 1
As shown in fig. 1-2, the invention provides a photovoltaic array fault detection and positioning method based on a time domain reflectometry, which comprises the following steps:
Preferably, the invention selects a square wave signal generator which generates a low-voltage high-speed step signal with the rise time of less than 10ns, the voltage amplitude of less than 5V and the frequency of less than 100KHz as a signal generating device, and selects a signal sampling device with the sampling rate of more than 50 MSPS.
It should be noted that, for the signal generating device and the signal sampling device in this step, any waveform function generator, DDS signal generator, self-made signal generating hardware circuit board, etc. capable of generating square wave signals meeting the detection requirements belong to the signal generating device, and any oscilloscope, ADC analog-to-digital converter, self-made analog signal sampling hardware circuit board, etc. meeting the signal sampling requirements belong to the signal sampling device.
and 4, continuously acquiring the waveform in the fault state: adjusting a sampling interval according to the size of the array to be detected, and acquiring a reflected signal waveform in a fault detection range through a signal acquisition device;
according to the method for adjusting the sampling interval, the propagation time t of an incident signal passing through a single photovoltaic module is about 100ns generally, and the incident signal is folded back in the photovoltaic array, so that the minimum sampling interval is set to be the number n x 2t0 of the modules in the photovoltaic array to be detected, and the maximum sampling interval is not more than n x 3t0, so that the signal waveform has enough resolution.
It should be noted that the wavelet threshold denoising algorithm may be implemented by using various software such as matlab and C + +, and the number of layers removed from a specific detail coefficient may be selected according to specific waveform characteristics, but at least the first 3 layers of detail coefficients need to be removed.
In this embodiment, the fault distance needs to be calculated by obtaining a signal time delay t when a signal passes through the photovoltaic array and is reflected back and a propagation velocity v of the signal in the photovoltaic array, and the specific steps are as follows: (1) The time when the signal rises rapidly is obtained as incident time delay t by calibration measurement 0 Obtaining the time when the reflected wave exceeds the threshold critical point as the reflection time delay t 1 And the propagation velocity v of the signal in the photovoltaic array; (2) Calculating to obtain the signal time delay t of the signal passing through the photovoltaic array and reflected back, wherein t = t 1 -t 0 (ii) a (3) Calculating the fault distance L of the fault point by a time delay estimation algorithm, wherein the specific calculation formula is
Thereby determining the location of the fault point.
Example 2
As shown in fig. 1-2, the invention provides a photovoltaic array fault detection and positioning method based on a time domain reflectometry, which comprises the following steps:
Preferably, the invention selects a square wave signal generator which generates a low-voltage high-speed step signal with the rise time of less than 10ns, the voltage amplitude of less than 5V and the frequency of less than 100KHz as a signal generating device, and selects a signal sampling device with the sampling rate of more than 50 MSPS.
It should be noted that, for the signal generating device and the signal sampling device in this step, any waveform function generator, DDS signal generator, self-made signal generating hardware circuit board, etc. capable of generating square wave signals meeting the detection requirements belong to the signal generating device, and any oscilloscope, ADC analog-to-digital converter, self-made analog signal sampling hardware circuit board, etc. meeting the signal sampling requirements belong to the signal sampling device.
and step 4, continuing to collect waveforms in the fault state: adjusting a sampling interval according to the size of the array to be detected, and acquiring a reflected signal waveform in a fault detection range through a signal acquisition device;
It should be noted that the denoising algorithm may be implemented by using various software such as matlab and C + +, and the number of layers for removing specific detail coefficients may be selected according to specific waveform characteristics, but at least the first 3 layers of detail coefficients need to be removed.
And 7, presetting a fault detection threshold, setting the fault detection threshold to be 5% -10% of the voltage amplitude of the step signal, judging whether a fault occurs according to the preset fault detection threshold and the signal amplitude obtained in the step 6, when the signal amplitude is larger than the fault detection threshold, the fault occurs, further calculating a fault distance L, and after the fault distance is calculated, determining the position of a fault point, and positioning and maintaining the fault point.
In this embodiment, the second method is adopted to calculate the fault distance, and in order to facilitate detection, the fault distance is often equivalent to the time delay t of a single photovoltaic module d Not only is
In the formula L d Substituting the formula into the formula of the delay estimation algorithm to obtain the signal propagation distance corresponding to the single component:
since the fault distance is positively correlated with the number of components, the positions of the available fault points are as follows:
where n is the position of the nth component in the photovoltaic array.
Specifically, the propagation time of the signal in a single photovoltaic module is determined by calibration measurements, i.e. selecting a standard photovoltaic module, injecting the signal into the measurement signal, measuring the time delay of the signal, and determining the time delay t corresponding to the single module d And positioning the fault point according to the signal time delay t obtained by detection and the photovoltaic array arrangement rule.
Example 3
The embodiment provides specific operations of the photovoltaic array fault detection and positioning method based on the time domain reflectometry, which comprise the following steps: the detection device is externally connected to the photovoltaic array to be detected, and comprises a signal acquisition device, a signal generation device, a T-shaped BNC three-way connector and a BNC-MC4 adapter, wherein the specific connection relationship is that the anodes of the signal generation device and the signal acquisition device are respectively connected with any two interfaces in the T-shaped BNC three-way connector, and the cathodes of the signal acquisition device and the signal generation device are connected with a photovoltaic array ground wire and a photovoltaic array metal frame when no ground wire exists; the positive pole of the signal generating device is connected to a BNC male joint on a 'BNC-MC 4' adapter through a T-shaped BNC three-way connector interface, an outgoing line of the BNC male joint is divided into a positive conducting wire and a negative conducting wire, the positive conducting wire is connected with a binding post of the MC4 adapter, and the negative conducting wire is connected with a photovoltaic module ground wire to complete a signal loop, in other words, the positive pole of the photovoltaic array is connected to the rest interface of the T-shaped BNC three-way connector through the 'BNC-MC 4' adapter interface. In this embodiment, the signal generating device selects any one of a waveform function generator, a DDS signal generator, and a self-made signal generating hardware circuit board of a square wave signal, and the signal sampling device selects any one of an oscilloscope, an ADC analog-to-digital converter, and a self-made analog signal sampling hardware circuit board.
Switching in the detection device, then electrifying, injecting a step signal sent by the signal generation device into the photovoltaic array to be detected through one interface in the T-shaped BNC three-way connector, and starting to detect whether the photovoltaic array has a fault and collect related data;
collecting a group of waveforms in a fault-free state, adjusting a sampling interval according to the size of the array to be detected, and collecting a group of waveforms of reflected signals of the photovoltaic array in the fault-free state after the sampling interval is adjusted, wherein the waveforms are used for calculating signal amplitude values;
collecting a waveform in a fault state: the sampling interval is adjusted according to the size of the array to be detected, and the reflected signal waveform in the fault detection range, namely the initial reflected waveform diagram, is obtained through the signal acquisition device, as shown in fig. 3. The illustrated fault detection type is photovoltaic array open circuit fault detection, and 8 groups of open circuit fault points are set in total and respectively: the connection between the photovoltaic direct current cable and the photovoltaic array is interrupted; the 7 groups of connections between the components are interrupted, and the last group is detected by the components close to the detection device, which are numbered from 1, starting from the interruption fault between the components 1 to 2, and ending with the interruption fault between the components 7 to 8.
In this embodiment, 8 groups of open circuit faults are used as samples, multiple types of faults such as short circuit and open circuit can be detected in the actual detection process, and meanwhile, specific component detection types and quantity are not limited in the actual detection, and the maximum detection range is based on the field detection result due to the difference between the measurement environment and the component parameters.
The initial reflection profile shown in fig. 3 can only approximate the failure point with a large detection error. Therefore, the noise influence in the signal needs to be eliminated, so that the fault detection precision is improved, and the specific denoising processing steps are as follows: denoising the reflected signal waveforms in the step 3 and the step 4 respectively by using a wavelet threshold denoising algorithm to obtain denoised reflected signal waveforms; the specific treatment steps are as follows: (1) Performing multi-layer wavelet decomposition on the original signal by using DB4 wavelet basis, and extracting approximate coefficient vector A = [ a ] of each layer 1 ,a 2 ,a 3 ,……,a n ]Extracting detail coefficient vector D = [ D ] of each layer 1 ,d 2 ,d 3 ,……,d n ](ii) a (2) To pair ofDenoising the detail coefficients of the noise signals, and removing at least the front 3 layers of detail coefficients to shield high-frequency parts in the signals in order to achieve proper signal waveform smoothness; (3) Wavelet reconstruction is carried out on the wavelet coefficient after denoising treatment, and an approximate coefficient a is utilized n And a detail coefficient d n And obtaining the denoised reflection signal waveform. Multiple reflections caused by the inconsistent impedance of the photovoltaic array itself are eliminated by this operation. And judging whether the fault occurs or not through the step E, and positioning a fault point.
It should be noted that the denoising algorithm may be implemented by using various software such as matlab, C + +, and the like, and a specific denoising threshold setting range is selected according to specific waveform characteristics, but in order to achieve suitable signal smoothness, at least the first 3 layers of detail coefficients are removed to mask a high-frequency part in the signal.
Obtaining a signal amplitude after denoising, and subtracting a sampling sequence of a photovoltaic array reflection signal waveform in a fault state from a sampling sequence of a photovoltaic array reflection signal waveform in a fault-free state to obtain a signal amplitude N sub,i The calculation expression is N sub,i ＝A si -A Ni In the formula A si And A Ni The amplitudes of the ith sampling point of the reflected signals of the fault-free system and the fault system are respectively. The application condition of the above formula is that the sampling standards of the photovoltaic array reflection waveforms in the fault state and the healthy state are the same.
The method comprises the steps of presetting a fault detection threshold value, wherein the preset fault detection threshold value is an amplitude threshold value, setting 5% -10% of a voltage amplitude of a step signal sent by a signal generation device as the fault detection threshold value, judging whether a fault occurs according to the preset fault detection threshold value and the signal amplitude value, when the signal amplitude value is larger than the fault detection threshold value, the fault occurs, further calculating a fault distance L, and determining the position of a fault point after calculating the fault distance to position and overhaul the fault point.
And the time when the reflected wave exceeds the threshold critical point is reflection time delay, the time when the signal generates a quick rising edge is incidence time delay, and the reflection time delay is subtracted from the incidence time delay to obtain the signal time delay when the signal passes through the photovoltaic array and is reflected back.
As shown in fig. 4, the reflection waveform result graph after denoising processing has obvious amplitude variation characteristics, a non-fault section in the photovoltaic array shows that the amplitude is near 0 in the image, when a fault occurs, the signal amplitude is rapidly reduced, and the fault is determined to occur when the signal amplitude exceeds the detection threshold.
Specifically, the time at which the signal generates the fast rising edge 1 is an incident time delay, the time at which the intersection point of the signal and the threshold is a reflection time delay, such as a breakpoint 2 between the dc cable and the photovoltaic module and an interruption fault 3 between the modules 1 to 2, and the dotted line 4 is a detection threshold. The signal time delay determines the fault distance through a time delay estimation algorithm, wherein the time delay estimation algorithm is expressed as follows:
wherein v is the propagation speed of the signal in the photovoltaic array, and t is the signal time delay.
Specifically, the propagation velocity v of the signal in the photovoltaic array is determined by calibration measurement, namely, a standard photovoltaic module and a photovoltaic direct current cable with a given length, such as a photovoltaic direct current cable with a length of 10m, are selected, the signal is injected into the photovoltaic module to measure the time delay of the signal in the photovoltaic module, and the positioning of any point is realized according to the signal time delay obtained by detection and the arrangement rule of the photovoltaic array.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (9)
1. A photovoltaic array fault detection and positioning method based on a time domain reflectometry method is characterized by comprising the following steps: the method comprises the following steps:
step 1, accessing a detection device: externally connecting a detection device to the photovoltaic array to be detected, and sending and collecting signals;
step 2, signal transmission: injecting a step signal sent by the detection device into the photovoltaic array to be detected through one interface in the T-shaped BNC three-way connector;
step 3, collecting the waveform in the non-fault state: adjusting a sampling interval according to the size of the array to be detected, and collecting a group of waveforms of the photovoltaic array reflected signals in a fault-free state;
step 4, collecting the waveform in the fault state: adjusting a sampling interval according to the scale of the array to be detected, and acquiring a reflected signal waveform in a fault detection range through a signal acquisition device;
step 5, denoising treatment: denoising the reflected signal waveforms in the step 3 and the step 4 respectively by using a wavelet threshold denoising algorithm to obtain denoised reflected signal waveforms;
step 6, obtaining a signal amplitude: after denoising, subtracting a sampling sequence of the waveform of the photovoltaic array reflected signal in the fault state from a sampling sequence of the waveform of the photovoltaic array reflected signal in the non-fault state to obtain a signal amplitude;
step 7, fault judgment and positioning: and (6) presetting a fault detection threshold, judging whether a fault occurs according to the preset fault detection threshold and the signal amplitude obtained in the step (6), if so, calculating a fault distance, and positioning a fault point according to the fault distance.
2. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: the detection device comprises a signal acquisition device, a signal generation device and a T-shaped BNC three-way connector, the anodes of the signal generation device and the signal acquisition device are respectively connected with any two interfaces in the T-shaped BNC three-way connector, the anode of the photovoltaic array is connected to the rest interface of the T-shaped BNC three-way connector, the cathodes of the signal acquisition device and the signal generation device are connected with a photovoltaic array ground wire or a photovoltaic array metal frame, and the cathodes are grounded.
3. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 2, wherein: the signal generating device adopts a square wave signal generator which generates step signals with the rise time of less than 10ns, the voltage amplitude of less than 5V and the frequency of less than 100 KHz.
4. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 2, wherein: the signal sampling means uses signal sampling means having a sampling rate greater than 50 MSPS.
5. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: the denoising processing in the step 4 comprises the following steps:
step 41: performing multi-layer wavelet decomposition on the original signal by using DB4 wavelet basis, and extracting approximate coefficient vector A = [ a ] of each layer 1 ,a 2 ,a 3 ,……,a n ]Extracting detail coefficient vector D = [ D ] of each layer 1 ,d 2 ,d 3 ,……,d n ]；
Step 42: denoising the detail coefficient containing the noise signal, and removing at least the detail coefficient of the front 3 layers;
step 43: wavelet reconstruction is carried out on the wavelet coefficient after denoising treatment, and an approximate coefficient a is utilized n And a detail coefficient d n And obtaining the denoised reflection signal waveform.
6. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: the signal amplitude calculation method in the step 6 comprises the following steps: n is a radical of hydrogen sub,i ＝A si -A Ni In the formula A si And A Ni The amplitudes of the ith sampling point of the reflected signals of the fault-free system and the fault system are respectively.
7. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: and setting the preset fault detection threshold value in the step 7 to be 5-10% of the voltage amplitude of the step signal, and judging that a fault occurs when the signal amplitude obtained in the step 6 is greater than the fault detection threshold value.
8. The method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: the fault distance in the step 7 is calculated by the following method:
(1) Obtaining the time when the signal rapidly rises as the incident time delay t 0 And obtaining the time when the reflected wave exceeds the threshold critical point as the reflection time delay t 1 And the propagation velocity v of the signal in the photovoltaic array;
(2) Calculating to obtain the signal time delay t of the signal passing through the photovoltaic array and reflected back, wherein t = t 1 -t 0 ；
(3) Calculating a fault distance L of a fault point, the fault distance L being calculated by the following formula,
9. the method for detecting and positioning the faults of the photovoltaic array based on the time domain reflectometry as claimed in claim 1, wherein: the fault distance in the step 7 is calculated by the following method:
(1) Calculating the total signal time delay t: obtaining the time when the signal rapidly rises as the incident time delay t 0 Obtaining the time when the reflected wave exceeds the threshold critical point as the reflection time delay t 1 Calculating to obtain the signal time delay t of the signal passing through the photovoltaic array and reflected back, wherein t = t 1 -t 0 ；
(2) Determining the time delay t corresponding to a single component d : selecting a standard photovoltaic module, injecting a step signal into the standard photovoltaic module, and measuring the corresponding time delay through calibration measurement, namely the time delay t corresponding to a single module d ；
(3) Calculating a fault distance n: calculating to obtain a fault distance n by the following formula, determining the position of a fault point,
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