CN113777448B - Method and device for determining arc fault occurrence time of photovoltaic module array - Google Patents
Method and device for determining arc fault occurrence time of photovoltaic module array Download PDFInfo
- Publication number
- CN113777448B CN113777448B CN202110907037.2A CN202110907037A CN113777448B CN 113777448 B CN113777448 B CN 113777448B CN 202110907037 A CN202110907037 A CN 202110907037A CN 113777448 B CN113777448 B CN 113777448B
- Authority
- CN
- China
- Prior art keywords
- arc fault
- photovoltaic module
- determining
- module array
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Photovoltaic Devices (AREA)
Abstract
The invention discloses a method and a device for determining arc fault occurrence time of a photovoltaic module array, wherein the method comprises the steps of processing a branch current waveform in a period of time when an arc occurs by adopting a PWVD algorithm, and drawing a PWVD two-dimensional graph; calculating the MAX value of the drawn PWVD two-dimensional graph; and comparing the MAX value with a preset threshold value, and judging the actual occurrence time of the arc fault of the photovoltaic module array. The method and the device can simply and quickly determine the occurrence time of the arc fault of the photovoltaic module.
Description
Technical Field
The invention relates to a method and a device for determining arc fault occurrence time of a photovoltaic module array, and belongs to the technical field of photovoltaic detection.
Background
The photovoltaic power generation system comprises a large number of photovoltaic modules, and the conditions of module aging, line aging, connection looseness and the like can occur in long-term operation, so that series or parallel arc faults of a photovoltaic module array can occur. These faults may cause accidents such as fire, and the safe and reliable operation of the photovoltaic power generation system is seriously affected.
Disclosure of Invention
The invention aims to provide a method and a device for determining the arc fault occurrence time of a photovoltaic module array, which are used for detecting the arc fault of the photovoltaic module array by utilizing a pseudo wigner distribution (PWVD) algorithm.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention provides a method for determining arc fault occurrence time of a photovoltaic module array, which comprises the following steps:
sampling the current of the photovoltaic module array;
preliminarily determining the time range of arc fault occurrence according to the sampled current waveform;
filtering and normalizing current data within the time range of the occurrence of the arc fault;
performing Hilbert transform on the processed current data;
processing the current data after Hilbert transformation by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
calculating the MAX value of each time point in the PWVD two-dimensional graph;
and judging the actual moment of the arc fault of the photovoltaic module array based on the MAX value.
Further, branch current of the photovoltaic module array is sampled, or current at a junction of the photovoltaic module array is sampled.
Further, 5s of photovoltaic module array current is collected, and the sampling frequency is 200kHz.
Further, a time range of 0.1s in which the arc fault occurred was preliminarily determined.
Further, the calculating MAX value of each time point in the PWVD two-dimensional map includes:
and summing and averaging the values of each column of the obtained PWVD two-dimensional graph to obtain the MAX value of the corresponding time point.
Further, the determining an actual time when the arc fault of the photovoltaic module array occurs based on the MAX value includes:
and comparing the MAX values with a preset threshold value one by one according to time, and if the MAX value is greater than the preset threshold value, determining a time point corresponding to the MAX value as an actual moment when the arc fault occurs.
Further, the threshold is set to 20.
The invention also provides a device for determining the arc fault occurrence time of the photovoltaic module array, which comprises the following components:
the sampling module is used for sampling the current of the photovoltaic module array;
the primary selection module is used for primarily determining the time range of the occurrence of the arc fault according to the sampled current waveform;
the first processing module is used for filtering and normalizing current data within a time range of arc fault occurrence;
the second processing module is used for carrying out Hilbert transform on the processed current data;
the third processing module is used for processing the current data after Hilbert transformation by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
the calculation module is used for calculating the MAX value of each time point in the PWVD two-dimensional graph;
and the number of the first and second groups,
and the judging module is used for judging the actual moment of the arc fault of the photovoltaic module array based on the MAX value.
Further, the computing module is specifically configured to,
and summing and averaging the values of each column of the obtained PWVD two-dimensional graph to obtain the MAX value of the corresponding time point.
Further, the judging module is specifically configured to,
and comparing the MAX values with a preset threshold value one by one according to time, and if the MAX value is greater than the preset threshold value, determining a time point corresponding to the MAX value as an actual moment when the arc fault occurs.
The invention has the following beneficial effects:
the invention provides a method for determining the arc fault occurrence time of a photovoltaic module array, which can judge the accurate arc fault occurrence time through a PWVD (pulse width modulation) diagram. By adopting the method, the arc fault occurrence time of the photovoltaic module can be simply and rapidly determined.
Drawings
FIG. 1 is a flow chart of a method for determining the occurrence time of an arc fault in a photovoltaic module array according to the present invention;
FIG. 2 is a graph of a photovoltaic circuit loop current waveform collected in an embodiment of the invention when an arc fault occurs;
FIG. 3 is a waveform of the loop current within 0.1s before and after an arc fault in an embodiment of the present invention;
FIG. 4 is a two-dimensional view of the PWVD corresponding to FIG. 3;
FIG. 5 is a two-dimensional graph of a PWVD corresponding to a loop current waveform in the absence of an arc fault condition in accordance with embodiments of the present invention;
fig. 6 is a graph plotting MAX values calculated in an embodiment of the present invention.
Detailed Description
The invention is further described below. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
One embodiment of the present invention provides a method for determining an arc fault occurrence time of a photovoltaic module array, which detects an actual occurrence time of an arc fault of the photovoltaic module array by using a pseudo wigner distribution (PWVD) algorithm, and the specific implementation process is as shown in fig. 1, including:
sampling an initial current of the photovoltaic component array;
determining the time range of the occurrence of the arc fault according to the initially sampled current waveform;
filtering and normalizing current data in the time range of the occurrence of the arc fault; performing Hilbert transform on the processed data;
processing the current data after Hilbert transformation by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
calculating the MAX value of each time point in the PWVD two-dimensional graph;
and judging the actual moment of the arc fault of the photovoltaic module array based on the MAX value.
In a preferred embodiment of the present invention, the initial current of the photovoltaic module array may be a branch current of the photovoltaic module array, or a bus current of the photovoltaic module array.
As a preferred embodiment of the present invention, the initial current of the photovoltaic module array may be a current within a time range of 5 s.
The PWVD two-dimensional graph is composed of a matrix, the color of the two-dimensional graph corresponds to the size of the matrix value, and the time range with obvious difference of the color is determined according to the color of the two-dimensional graph and is used as the time range of the initially selected arc fault.
As a preferred embodiment of the present invention, the time range of the initial selection of the arc fault occurrence may be selected from a time range of 0.1 s.
In a preferred embodiment of the present invention, the MAX value is calculated as a mean value of a sum of matrix values corresponding to all vertical coordinates of the PWVD two-dimensional graph under the condition that the horizontal coordinates are unchanged, and all horizontal coordinates correspond to a series of MAX values.
In a preferred embodiment of the present invention, a threshold is set, the MAX value is compared with the threshold one by one in time, and if the MAX value is greater than the threshold, the time on the horizontal axis corresponding to the MAX value is determined as the actual time when the arc fault occurs.
As a preferred embodiment of the present invention, the threshold value is set to 20.
Examples
By taking the collection of the current of the string branch of the photovoltaic module for 5s as an example, fig. 2 shows a time-varying graph of the current when the photovoltaic circuit generates an arc, and the sampling rate is 200kHz. The first step is to carry out the preliminary processing of the data on the collected data, and carry out the filtering and normalization processing on the data; secondly, performing Hilbert transform on the data obtained in the first step; the-0.1 s to 0s period of fig. 2 and including the total 0.1s current at the time of arc occurrence is taken as in fig. 3. And the third step is to carry out the PWVD algorithm processing on the current waveform selected in the second step to obtain a PWVD diagram as shown in figure 4, and for comparison, a PWVD conversion diagram of the current from-1 s to-0.90 s under the normal condition is shown in figure 5. The fourth step refers to the value "MAX" for processing in order to identify the data when the arc fault occurs. Since the picture is composed of a matrix, the different colors represent different numbers of the matrix. The "MAX" value is obtained by averaging the values of each column of the obtained PWVD map, and for example, fig. 6 shows the "MAX" value from-0.1 s to 0s, and the arc fault can be distinguished by comparing the "MAX" value, and the arc occurrence time is-0.02 s, which corresponds to the arc occurrence time in fig. 2. And if the 'MAX' value is larger than the threshold value a, the arc is judged to be generated.
Another embodiment of the present invention further provides a device for determining an arc fault occurrence time of a photovoltaic module array, including:
the sampling module is used for sampling the array current of the photovoltaic module;
the primary selection module is used for primarily determining the time range of the occurrence of the arc fault according to the sampled current waveform;
the first processing module is used for filtering and normalizing current data in a time range of occurrence of the arc fault;
the second processing module is used for carrying out Hilbert transform on the processed current data;
the third processing module is used for processing the current data after Hilbert conversion by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
the calculation module is used for calculating the MAX value of each time point in the PWVD two-dimensional graph;
and (c) a second step of,
and the judging module is used for judging the actual moment when the arc fault of the photovoltaic module array occurs based on the MAX value.
As a preferred embodiment of the invention, the calculation module is specifically adapted to,
and summing and averaging the values of each column of the obtained PWVD two-dimensional graph to obtain the MAX value of the corresponding time point.
As a preferred embodiment of the present invention, the determining module is specifically configured to,
and comparing the MAX values with a preset threshold value one by one according to time, and if the MAX value is greater than the preset threshold value, determining a time point corresponding to the MAX value as an actual moment when the arc fault occurs.
It should be noted that the embodiment of the apparatus corresponds to the embodiment of the method, and the implementation manners of the embodiment of the method are all applicable to the embodiment of the apparatus and can achieve the same or similar technical effects, so that the detailed description is omitted here.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (8)
1. A method of determining when an arc fault of a photovoltaic module array occurs, comprising:
sampling the current of the photovoltaic module array;
preliminarily determining the time range of arc fault occurrence according to the sampled current waveform;
filtering and normalizing current data within the time range of the occurrence of the arc fault;
performing Hilbert transform on the processed current data;
processing the current data after Hilbert transformation by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
calculating the MAX value of each time point in the PWVD two-dimensional map, wherein the MAX value comprises the following steps: summing and averaging the values of each column of the obtained PWVD two-dimensional graph to obtain the MAX value of the corresponding time point;
and judging the actual moment of the arc fault of the photovoltaic module array based on the MAX value.
2. The method for determining the arc fault occurrence time of the photovoltaic module array according to claim 1, wherein the branch current of the photovoltaic module array or the current at the confluence of the photovoltaic module array is sampled.
3. The method for determining the occurrence time of the arc fault of the photovoltaic module array as claimed in claim 1, wherein the photovoltaic module array current is collected for 5s, and the sampling frequency is 200kHz.
4. The method for determining the occurrence moment of the arc fault of the photovoltaic module array according to claim 1, wherein the time range of 0.1s of the occurrence moment of the arc fault is preliminarily determined.
5. The method for determining the arc fault occurrence time of the photovoltaic module array according to claim 1, wherein the determining the actual arc fault occurrence time of the photovoltaic module array based on the MAX value comprises:
and comparing the MAX value with a preset threshold value one by one according to time, and if the MAX value is greater than the preset threshold value, determining a time point corresponding to the MAX value as an actual moment when the arc fault occurs.
6. The method for determining the occurrence time of the arc fault of the photovoltaic module array according to claim 5, wherein the threshold value is set to 20.
7. An apparatus for determining a time when an arc fault of a photovoltaic module array occurs, comprising:
the sampling module is used for sampling the array current of the photovoltaic module;
the primary selection module is used for preliminarily determining the time range of the arc fault according to the sampled current waveform;
the first processing module is used for filtering and normalizing current data within a time range of arc fault occurrence;
the second processing module is used for carrying out Hilbert transform on the processed current data;
the third processing module is used for processing the current data after Hilbert conversion by adopting a PWVD algorithm to obtain a PWVD two-dimensional graph;
the calculation module is used for calculating the MAX value of each time point in the PWVD two-dimensional graph, and specifically comprises the following steps: summing and averaging the values of each column of the obtained PWVD two-dimensional graph to obtain a MAX value corresponding to a time point;
and the number of the first and second groups,
and the judging module is used for judging the actual moment of the arc fault of the photovoltaic module array based on the MAX value.
8. The apparatus for determining the occurrence time of the arc fault of the photovoltaic module array according to claim 7, wherein the determining module is specifically configured to,
and comparing the MAX value with a preset threshold value one by one according to time, and if the MAX value is greater than the preset threshold value, determining a time point corresponding to the MAX value as an actual moment when the arc fault occurs.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110907037.2A CN113777448B (en) | 2021-08-09 | 2021-08-09 | Method and device for determining arc fault occurrence time of photovoltaic module array |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110907037.2A CN113777448B (en) | 2021-08-09 | 2021-08-09 | Method and device for determining arc fault occurrence time of photovoltaic module array |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113777448A CN113777448A (en) | 2021-12-10 |
| CN113777448B true CN113777448B (en) | 2023-04-14 |
Family
ID=78837046
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110907037.2A Active CN113777448B (en) | 2021-08-09 | 2021-08-09 | Method and device for determining arc fault occurrence time of photovoltaic module array |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113777448B (en) |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5121282A (en) * | 1990-03-30 | 1992-06-09 | White Orval C | Arcing fault detector |
| JP2834071B2 (en) * | 1996-05-13 | 1998-12-09 | 日本電気株式会社 | Target signal automatic detection method and device |
| CN107783013A (en) * | 2016-08-30 | 2018-03-09 | 上海复旦微电子集团股份有限公司 | A kind of detection method and device of arc fault |
| CN107086855B (en) * | 2017-04-25 | 2018-10-30 | 西安交通大学 | The photovoltaic system fault arc detection method of more time-frequency characteristics is merged in a kind of machine learning |
| CN107991660B (en) * | 2017-11-29 | 2021-06-22 | 南京理工大学 | Intermediate trajectory projectile velocity measurement method based on PWVD distribution |
| CN112363021B (en) * | 2020-11-13 | 2022-05-17 | 重庆大学 | Distributed line fault detection and positioning system and method |
-
2021
- 2021-08-09 CN CN202110907037.2A patent/CN113777448B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113777448A (en) | 2021-12-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109194286B (en) | Fault diagnosis method and device for photovoltaic module | |
| CN111983381A (en) | Power cable line cross interconnection box fault positioning method and device | |
| CN112532643B (en) | Flow anomaly detection method, system, terminal and medium based on deep learning | |
| CN113156336B (en) | Method and device for identifying single-tube open-circuit fault of Vienna rectifier in two stages and storage medium | |
| CN112379213A (en) | Fault detection method and system | |
| CN114726642B (en) | Quantification system based on network threat of power monitoring system | |
| CN113777448B (en) | Method and device for determining arc fault occurrence time of photovoltaic module array | |
| CN109142979B (en) | Method and device for detecting abnormal state of power distribution network | |
| CN109901003B (en) | Inverter power fault detection method and system | |
| CN111722053A (en) | Multi-energy complementary micro-grid fault rapid identification method and system | |
| CN107332267A (en) | It is a kind of to avoid extra-high voltage direct-current power from continuing relatively low control method and system | |
| CN113884943B (en) | Leakage fault analysis method, device, equipment and medium | |
| CN109412901B (en) | Method and system for detecting continuity of acquired data based on time domain processing | |
| CN110687344B (en) | Single-phase voltage sag detection method and device, voltage restorer, equipment and medium | |
| CN110095743B (en) | Distribution network terminal wave recording performance test module and waveform fitting method thereof | |
| CN110148065B (en) | Short-circuit current calculation processing method and system considering flexible and direct influence | |
| CN112415258A (en) | Method and system for judging characteristic amplitude and duration of voltage transient event | |
| CN116979528B (en) | Method, device and medium for quickly starting low-voltage ride through of power electronic converter | |
| CN112086933B (en) | ADC abnormal data discrimination method and device applied to relay protection device | |
| CN104699572A (en) | Computer hardware diagnosis method based on UNIX operating system | |
| CN114019321B (en) | DC series arc fault detection method and device based on normalized standard deviation and wavelet entropy | |
| CN115221472B (en) | Self-adaptive setting method and device for user voltage limit value, memory and computing equipment | |
| CN111157790B (en) | Power system harmonic detection device and method based on deep learning | |
| CN116409609A (en) | Photovoltaic equipment fault sensing method and device, electronic equipment and storage medium | |
| CN118169504A (en) | Abnormal node fault reporting information determining system and method in cable monitoring |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |