Photovoltaic power station DC fault arc monitoring device

Abstract

The invention discloses a photovoltaic power station direct current fault arc monitoring device, which comprises a track installation assembly and a monitoring device main body, and is characterized in that the track installation assembly realizes flexible installation and convenient maintenance of the monitoring device through a guide rail, a roller and a clamping groove structure; the arc signal acquisition module integrates a plurality of functional modules, and adopts a Hall current sensor circuit and a voltage division type voltage sensor circuit to accurately acquire signals; the signal processing module filters and amplifies the collected signals and extracts fault arc characteristic parameters; the fault judgment module carries out fault recognition through a threshold judgment method in combination with wavelet analysis and a neural network algorithm; the communication module realizes stable data transmission by switching a wireless communication mode and a wired communication mode; the power supply module combines a DC conversion circuit, a power supply management unit and a standby power supply unit to guarantee continuous power supply. The problems that an existing monitoring device is inconvenient to install, low in monitoring precision, high in fault misjudgment rate, limited in data transmission, unstable in power supply and the like are solved.

Description

Technical Field

[0001] The present invention relates to an arc monitoring device, in particular to a DC fault arc monitoring device for a photovoltaic power station. Background Art

[0002] In the operation and maintenance of photovoltaic power stations, DC arc fault monitoring devices are used to collect arc signals, analyze and determine arc faults, and issue warnings to avoid accidents such as fires caused by arc faults. Existing DC arc fault monitoring devices have the following technical problems:

[0003] (1) Most of them adopt fixed installation structures, such as directly connecting to the bracket or cabinet with bolts. During installation, disassembly and subsequent maintenance, the power needs to be turned off and a lot of time is spent on disassembly and assembly, which makes the installation flexibility poor; (2) In terms of signal acquisition, the sensor circuit has insufficient ability to capture weak arc signals in complex DC environments and is easily interfered by noise; (3) The signal is only filtered and amplified for basic processing, and subsequent fault judgment relies on traditional threshold comparison methods, which may cause misjudgment and missed judgment; (4) It only supports wired or a few wireless communication methods. Faced with the complex layout of photovoltaic power stations, the stability and adaptability of data transmission are limited; (5) The power module has no backup design. When the main power fails, the monitoring device stops operating and cannot continue monitoring. Summary of the Invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a photovoltaic power station DC fault arc monitoring device to solve one or more technical problems existing in the prior art.

[0005] Technical solution: A photovoltaic power station DC fault arc monitoring device of the present invention includes a track mounting assembly and a monitoring device body. The track mounting assembly includes a guide rail and a mounting bracket. The guide rail is fixed to the bearing structure by means of expansion bolts; the mounting bracket is slidingly set on the guide rail by means of rollers, and the monitoring device body can be detachably fixed to the mounting bracket.

[0006] Furthermore, a slot adapted to the monitoring device body is provided on the mounting bracket, and the monitoring device body is snapped into the slot and locked by a fastening bolt.

[0007] Furthermore, the main housing of the monitoring device is made of aluminum alloy and has an IP65 protection grade.

[0008] Furthermore, the monitoring device body is provided with an arc signal acquisition module, a signal processing module, a fault judgment module, a communication module and a power supply module;

[0009] The arc signal acquisition module includes a Hall current sensor circuit and a voltage divider voltage sensor circuit, which are used to collect current signals and voltage signals in the DC circuit of the photovoltaic power station respectively;

[0010] The signal processing module is used to filter and amplify the collected current and voltage signals and extract the fault arc characteristic parameters, which include current mutation characteristics and voltage fluctuation characteristics;

[0011] The fault judgment module is used to compare the extracted fault arc characteristic parameters with the preset fault arc characteristic threshold. When the fault arc characteristic parameters exceed the preset threshold, it is determined that a fault arc may have occurred. The fault judgment is further performed by combining wavelet analysis and neural network algorithm.

[0012] The communication module uses switchable wireless communication circuits and wired communication circuits to send fault arc judgment results to the monitoring center of the photovoltaic power station;

[0013] The power supply module is used to provide working power for the arc signal acquisition module, signal processing module, fault judgment module and communication module. It includes a DC conversion circuit, a power management unit and a backup power supply unit. The DC conversion circuit converts the DC power of the photovoltaic power station into the voltage required by each module, and the power management unit realizes the voltage stabilization and overload protection functions of the power supply.

[0014] Furthermore, the signal processing module includes a signal filtering unit, a signal amplification unit and a feature extraction unit. The signal filtering unit is used to filter the collected current and voltage signals to remove noise interference; the signal amplification unit amplifies the filtered current and voltage signals to achieve signal enhancement; the feature extraction unit is used to extract the fault arc characteristic parameters in the amplified current and voltage signals.

[0015] Furthermore, the signal filtering unit adopts an RC filtering circuit or an active filtering circuit; the signal amplifying unit adopts an amplifying circuit composed of operational amplifiers; and the feature extraction unit uses a fast Fourier transform algorithm to extract the fault arc feature parameters.

[0016] Furthermore, the wavelet analysis algorithm captures the time-frequency characteristics of the arc signal. The neural network uses the characteristic parameters extracted by the wavelet analysis algorithm as input and the classification result of the fault arc as output, and the classification result is faulty or normal.

[0017] Furthermore, the wireless communication circuit adopts a LoRa communication circuit, a 4G / 5G communication circuit or a Wi-Fi communication circuit, and the wired communication circuit adopts an RS485 communication circuit or an Ethernet communication circuit.

[0018] Furthermore, the communication module gives priority to wireless communication. When there are multiple wireless communication methods, it selects according to signal stability, coverage and real-time transmission requirements; if the wireless communication is interrupted, it automatically switches to the wired communication circuit.

[0019] Furthermore, the backup power supply unit adopts a rechargeable battery.

[0020] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0021] (1) The mounting bracket can be moved along the guide rail, and the monitoring device body and the mounting bracket can be detachably connected, thereby realizing flexible installation and convenient maintenance of the monitoring device.

[0022] (2) The Hall current sensor circuit and the voltage divider voltage sensor circuit are used to collect arc signals, which have strong ability to capture weak arc signals and strong anti-interference ability.

[0023] (3) After signal filtering and amplification, key fault arc characteristic parameters, such as current mutation characteristics and voltage fluctuation characteristics, are extracted in a targeted manner. A preliminary arc fault judgment is made based on the preset fault arc characteristic threshold. The fault is then identified by combining wavelet analysis and neural network algorithm, resulting in a higher fault identification accuracy.

[0024] (4) The communication module achieves stable data transmission through switchable wireless communication circuits and wired communication circuits.

[0025] (5) The power module combines the DC conversion circuit, power management unit and backup power unit to ensure continuous power supply.

[0026] In summary, the present invention effectively solves the problems of existing DC fault arc monitoring devices, such as inconvenient installation, susceptibility to signal interference (low monitoring accuracy), high fault misjudgment rate, data transmission limitations and poor power supply reliability, and greatly improves the efficiency and reliability of DC fault arc monitoring in photovoltaic power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of the structure of the track installation assembly and the monitoring device body in an embodiment of the present invention;

[0028] Figure 2 This is a module structure diagram of a DC fault arc monitoring device for a photovoltaic power station according to an embodiment of the present invention;

[0029] Figure 3 This is a timing diagram of signal processing and fault judgment of a DC fault arc monitoring device for a photovoltaic power station according to an embodiment of the present invention;

[0030] Figure 4 This is a timing diagram of the power supply logic of the power module in an embodiment of the present invention;

[0031] Figure 5 4 is a data transmission flow chart of the communication module in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below with reference to the accompanying drawings.

[0033] Attachment Figures 1 to 5 The reference numerals in the figures are as follows:

[0034] 1. Guide rail; 2. Mounting bracket; 3. Monitoring device body.

[0035] like Figures 1 to 5 As shown, an embodiment of the present invention provides a photovoltaic power station DC fault arc monitoring device, including a track installation component and a monitoring device body 3, and the track installation component includes a guide rail 1 and a mounting bracket 2.

[0036] Guide rail 1 is fixed to a load-bearing structure such as a photovoltaic power station support or wall using expansion bolts. Mounting bracket 2 is slidably mounted on guide rail 1 using rollers. Monitoring device body 3 is detachably fixed to mounting bracket 2. Specifically, mounting bracket 2 is provided with a slot adapted for monitoring device body 3. Monitoring device body 3 is snapped into the slot and locked with a tightening bolt.

[0037] The monitoring device body 3 can be adjusted along the guide rail 1 to accommodate photovoltaic strings of different spacings. The monitoring device body 3 is detachably connected to the mounting bracket 2, shortening installation and maintenance time, and no power outage is required during installation and maintenance.

[0038] To ensure that the arc monitoring device can operate stably in complex outdoor environments, in this embodiment, the outer shell of the monitoring device body 3 is made of aluminum alloy and has an IP65 protection level, which is dustproof and waterproof, and can resist erosion by wind, sand and rain.

[0039] The monitoring device body 3 is internally provided with an arc signal acquisition module, a signal processing module, a fault judgment module, a communication module and a power supply module. Each module is described in detail below.

[0040] (1) Arc signal acquisition module

[0041] The arc signal acquisition module includes a current sensor circuit and a voltage sensor circuit. The current sensor circuit is connected in series to the DC circuit of the photovoltaic power station to collect the current signal in the DC circuit of the photovoltaic power station. The voltage sensor circuit is connected in parallel to the DC circuit of the photovoltaic power station to collect the voltage signal in the DC circuit of the photovoltaic power station.

[0042] In this embodiment, the current sensor circuit uses a Hall effect current sensor circuit, and the voltage sensor circuit uses a voltage divider voltage sensor circuit or a Hall effect voltage sensor circuit, preferably a voltage divider voltage sensor circuit. The Hall effect current sensor circuit has strong anti-interference capabilities and can accurately detect sudden changes in arc current at the microampere level. The voltage divider voltage sensor circuit has a fast response speed and can sensitively detect voltage fluctuations.

[0043] Current sensor circuits and voltage sensor circuits complement each other in arc fault monitoring. The current sensor circuit accurately captures current signal changes generated by arcing, while the voltage sensor circuit monitors voltage fluctuations. Sudden current changes are often accompanied by voltage fluctuations. Synchronous detection of the two provides a more comprehensive and accurate arc fault signal. This collaborative operation effectively avoids signal loss or misjudgment caused by a single sensor, improving the accuracy of arc fault detection.

[0044] The DC arc fault monitoring device for a photovoltaic power plant must be electrically connected to existing equipment, such as the plant's DC combiner box and DC distribution cabinet. During installation, adjust the mounting bracket 2 on the guide rail 1, align the monitoring device body 3 with the DC line to be tested in the plant's DC combiner box or DC distribution cabinet, and then connect the arc signal acquisition module's current sensor circuit in series with the DC line, and the voltage sensor circuit in parallel with the DC line.

[0045] (2) Signal processing module

[0046] The signal processing module includes a signal filtering unit, a signal amplification unit and a feature extraction unit. The signal filtering unit is used to filter the collected current and voltage signals to remove noise interference; the signal amplification unit amplifies the filtered current and voltage signals to achieve signal enhancement; the feature extraction unit is used to extract the fault arc characteristic parameters from the amplified current and voltage signals. The fault arc characteristic parameters include current mutation characteristics, voltage fluctuation characteristics, etc.

[0047] In this embodiment, the signal filtering unit uses a fourth-order Butterworth active filter circuit to perform bandpass filtering on the signal, removing 50Hz power frequency interference and high-frequency clutter. The signal amplification unit uses an in-phase proportional amplifier circuit composed of an OP07 operational amplifier to amplify the signal amplitude by 100 times. The feature extraction unit uses a fast Fourier transform algorithm to extract the characteristic parameters of the fault arc within the 10kHz to 1MHz frequency band.

[0048] (3) Fault diagnosis module

[0049] The fault diagnosis module compares the extracted arc fault characteristic parameters with the preset arc fault characteristic threshold as a preliminary judgment standard, enabling rapid screening of the possibility of arc faults. When the arc fault characteristic parameters (such as current mutation characteristics and voltage fluctuation characteristics) exceed the preset threshold, it is determined that an arc fault may have occurred. Because arc signals may be subject to noise interference or weak signals, a single threshold comparison may not accurately identify all faults, resulting in misjudgments or missed judgments. Therefore, wavelet analysis and neural network algorithms are further combined for fault diagnosis to improve the accuracy of fault judgment.

[0050] Specifically, the wavelet analysis algorithm performs time-frequency decomposition on the collected arc signal, extracting its transient characteristics (such as sudden changes in current or voltage). This is particularly useful for identifying weak or short-duration arc signals. By analyzing the signal at multiple scales, wavelet analysis can accurately capture the time-frequency characteristics of the arc signal, enhancing the system's ability to identify small arc faults.

[0051] At the same time, the neural network algorithm is trained to build a fault signature library by studying historical fault arc data and normal operation data. The neural network input is the characteristic parameters extracted by wavelet analysis, and the output is the fault arc classification result (faulty or normal). By training on a large amount of historical data, the neural network can automatically adjust the fault judgment criteria, improving the accuracy and intelligence of fault judgment.

[0052] Wavelet analysis is used for signal feature extraction, while neural networks are used for pattern recognition. Both algorithms are widely used in the prior art. This invention combines wavelet analysis and neural network algorithms to improve the system's fault identification accuracy and enhance the precision and robustness of arc fault judgment.

[0053] The fault judgment module uses threshold comparison as a preliminary screening, combined with the comprehensive algorithm of wavelet analysis and neural network to intelligently and accurately identify fault arcs, reducing misjudgments and missed judgments.

[0054] (4) Communication module

[0055] The communication module utilizes switchable wireless and wired communication circuits to transmit arc fault detection results to the PV power plant's monitoring center. The wireless communication circuit enables real-time data transmission within a 5km range, while the wired communication circuit ensures communication stability even in electromagnetic interference environments. The system supports dual-mode switching, ensuring 99.9% data transmission reliability.

[0056] In this embodiment, the communication module configuration is flexible. Users can select wireless communication circuits (such as LoRa communication circuits, 4G / 5G communication circuits, or Wi-Fi communication circuits) or wired communication circuits (such as RS485 communication circuits or Ethernet communication circuits) based on actual application scenarios and requirements. In actual applications, the monitoring device only needs to be configured with one of the wireless communication circuits and one wired communication circuit. The specific selection depends on the network conditions and requirements of the photovoltaic power station.

[0057] For example, consider a scenario where wireless communication uses LoRa and wired communication uses RS485. The communication module is configured with a preset communication priority, prioritizing wireless communication because it can more flexibly adapt to deployment requirements at different locations within a PV power plant. When wireless communication is available, the system prioritizes LoRa (433MHz) communication to send fault information to a LoRa gateway within the PV power plant, which then transmits it to a monitoring center via a fiber optic network. When multiple wireless communication methods are available (such as LoRa, 4G / 5G, and Wi-Fi), the system prioritizes the most appropriate wireless communication method based on signal stability, coverage, and real-time transmission requirements. If wireless communication is unavailable, the system switches to RS485 wired communication, using the PV power plant's existing Ethernet industrial switches to transmit data to the monitoring center. For wired communication, RS485 is preferred. However, other wired communication methods (such as Ethernet) may be used if environmental requirements or network conditions are unique. The most appropriate communication method is selected based on the specific deployment environment of the PV power plant.

[0058] After receiving the fault alarm information through the SCADA system of the monitoring center, the operation and maintenance personnel can locate the fault location in conjunction with the GIS map, go to the site with a handheld terminal, use the handheld terminal to communicate with the debugging interface on the monitoring device body 3, read the detailed fault data for analysis and processing, and at the same time, by adjusting the position of the mounting bracket 2 on the guide rail 1, move the monitoring device to other lines to be tested for detection, thereby realizing comprehensive monitoring of the DC lines of the photovoltaic power station.

[0059] (5) Power module

[0060] The power supply module provides operating power for the arc signal acquisition module, signal processing module, fault diagnosis module, and communication module. It includes a DC conversion circuit, a power management unit, and a backup power supply unit. The DC conversion circuit input is connected to the DC busbar of the photovoltaic power station, converting the 300-1000V DC power input from the DC busbar to voltages such as 5V and 12V suitable for each module. The power management unit implements functions such as power supply voltage stabilization and overload protection. The backup power supply unit is connected in parallel with the power management unit and uses a rechargeable battery, such as a lithium iron phosphate battery, to maintain a floating charge state. In the event of a main power failure in the photovoltaic power station, it provides a short-term emergency power supply (continuous power supply for more than 8 hours) to the photovoltaic power station DC fault arc monitoring device to ensure monitoring continuity.

Claims

1. A photovoltaic power station DC fault arc monitoring device, characterized in that: The invention comprises a track installation component and a monitoring device body (3), wherein the track installation component comprises a guide rail (1) and a mounting bracket (2), wherein the guide rail (1) is fixed to a bearing structure by means of expansion bolts; the mounting bracket (2) is slidingly arranged on the guide rail (1) by means of rollers, and the monitoring device body (3) is detachably fixed to the mounting bracket (2).

2. The photovoltaic power station DC fault arc monitoring device according to claim 1, characterized in that: A slot adapted to the monitoring device body (3) is provided on the mounting bracket (2); the monitoring device body (3) is engaged in the slot and locked by a fastening bolt.

3. The photovoltaic power station DC fault arc monitoring device according to claim 1, characterized in that: The housing of the monitoring device body (3) is made of aluminum alloy and has an IP65 protection grade.

4. The photovoltaic power station DC fault arc monitoring device according to claim 1, characterized in that: The monitoring device body (3) is internally provided with an arc signal acquisition module, a signal processing module, a fault judgment module, a communication module and a power supply module; The arc signal acquisition module includes a Hall current sensor circuit and a voltage divider voltage sensor circuit, which are used to collect current signals and voltage signals in the DC circuit of the photovoltaic power station respectively; The signal processing module is used to filter and amplify the collected current and voltage signals and extract the fault arc characteristic parameters, which include current mutation characteristics and voltage fluctuation characteristics; The fault judgment module is used to compare the extracted fault arc characteristic parameters with the preset fault arc characteristic threshold. When the fault arc characteristic parameters exceed the preset threshold, it is determined that a fault arc may have occurred. The fault judgment is further performed by combining wavelet analysis and neural network algorithm. The communication module uses switchable wireless communication circuits and wired communication circuits to send fault arc judgment results to the monitoring center of the photovoltaic power station; The power supply module is used to provide working power for the arc signal acquisition module, signal processing module, fault judgment module and communication module. It includes a DC conversion circuit, a power management unit and a backup power supply unit. The DC conversion circuit converts the DC power of the photovoltaic power station into the voltage required by each module, and the power management unit realizes the voltage stabilization and overload protection functions of the power supply.

5. The photovoltaic power station DC fault arc monitoring device according to claim 4, characterized in that: The signal processing module includes a signal filtering unit, a signal amplification unit and a feature extraction unit. The signal filtering unit is used to filter the collected current and voltage signals to remove noise interference; the signal amplification unit amplifies the filtered current and voltage signals to achieve signal enhancement; the feature extraction unit is used to extract the fault arc characteristic parameters from the amplified current and voltage signals.

6. The photovoltaic power station DC fault arc monitoring device according to claim 5, characterized in that: The signal filtering unit adopts an RC filtering circuit or an active filtering circuit; the signal amplifying unit adopts an amplifying circuit composed of operational amplifiers; and the feature extraction unit uses a fast Fourier transform algorithm to extract the characteristic parameters of the fault arc.

7. The photovoltaic power station DC fault arc monitoring device according to claim 4, characterized in that: The wavelet analysis algorithm captures the time-frequency characteristics of the arc signal. The neural network uses the characteristic parameters extracted by the wavelet analysis algorithm as input and the classification result of the fault arc as output, and the classification result is faulty or normal.

8. The photovoltaic power station DC fault arc monitoring device according to claim 4, characterized in that: The wireless communication circuit adopts LoRa communication circuit, 4G / 5G communication circuit or Wi-Fi communication circuit, and the wired communication circuit adopts RS485 communication circuit or Ethernet communication circuit.

9. The photovoltaic power station DC fault arc monitoring device according to claim 4, characterized in that: The communication module gives priority to wireless communication. When there are multiple wireless communication methods, it selects according to signal stability, coverage and real-time transmission requirements; if wireless communication is interrupted, it automatically switches to the wired communication circuit.

10. The photovoltaic power station DC fault arc monitoring device according to claim 4, characterized in that: The backup power supply unit uses a rechargeable battery.

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