Distributed photovoltaic power station DC arc on-line monitoring system and method

Abstract

The invention discloses a distributed photovoltaic power station direct current arc on-line monitoring system and method. The system comprises a voltage transformer, a current sensor, an optical fiber temperature sensor, a magneto-dependent sensor, a signal processing module, a central control unit and a human-computer interaction interface. The voltage transformer, the current sensor, the optical fiber temperature sensor and the magneto-dependent sensor are installed at the monitoring position of the distributed photovoltaic power station, and the output ends of the voltage transformer, the current sensor, the optical fiber temperature sensor and the magneto-dependent sensor are connected with the input end of the signal processing module. The output end of the signal processing module is connected with the input end of the central control unit, the output end of the central control unit is connected with the human-computer interaction interface, and the system and the method can intelligently, accurately and efficiently monitor the direct-current arc of the distributed photovoltaic power station.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of distributed photovoltaic power generation, and relates to a distributed photovoltaic power station direct current arc online monitoring system and method. BACKGROUND

[0002] Under the trend of energy transformation today, distributed photovoltaic power stations have developed rapidly. With the continuous expansion of installed capacity, its safe and stable operation has attracted more and more attention, and the problem of direct current arc has become the focus of the industry.

[0003] In the prior art, some early distributed photovoltaic power stations mainly rely on traditional electrical protection devices to indirectly prevent direct current arc hazards. For example, fuses and circuit breakers are often used for overcurrent protection, which cut off the circuit when the circuit current exceeds the preset threshold to prevent excessive current caused by arcs from damaging the line. At the same time, some power stations use simple temperature sensors placed at key connection points to try to infer possible arc faults by monitoring abnormal temperature rises, because arc generation is often accompanied by local overheating.

[0004] However, these existing technologies have many shortcomings. The reaction mechanism of traditional fuses and circuit breakers is relatively slow, and for slowly developing direct current arcs, it is difficult to quickly detect them in their initial stage. Since the fault current of direct current arcs rises relatively slowly compared to alternating current, it is possible that the arc has existed and caused hidden damage to the equipment before the overcurrent protection action value is reached, and after accumulating over time, it can cause serious faults such as burning out the junction box and damaging the photovoltaic modules. And the temperature sensor is greatly disturbed by environmental factors, and in high temperature environments or under normal heating conditions of photovoltaic modules, it is difficult to accurately distinguish temperature abnormalities caused by direct current arcs, resulting in a high false alarm rate, making it difficult for maintenance personnel to accurately determine the root cause of the fault in a timely manner, increasing unnecessary maintenance costs and time loss. Moreover, most existing technologies lack the ability to analyze arc characteristics in detail, and cannot capture key information such as changes in electrical parameters and spectral characteristics of arcs in real time, making it difficult to accurately locate and early warn direct current arcs, and unable to meet the safety protection needs of distributed photovoltaic power stations under complex and variable working conditions.

[0005] In summary, the existing monitoring methods for direct current arcs in distributed photovoltaic power stations have been unable to adapt to the development of the industry, and there is an urgent need for an online monitoring system and method that is more intelligent, accurate and efficient. SUMMARY

[0006] The present application aims to overcome the shortcomings of the prior art and provides a distributed photovoltaic power station direct current arc online monitoring system and method that can intelligently, accurately and efficiently monitor direct current arcs in distributed photovoltaic power stations.

[0007] In order to achieve the above purpose, the application discloses a kind of distributed photovoltaic power station direct current arc on-line monitoring system, including voltage transformer, current sensor, optical fiber temperature sensor, magnetic sensor, signal processing module, central control unit and man-machine interface;

[0008] The voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are installed at the monitoring position of the distributed photovoltaic power station, and the output ends of the voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are connected with the input end of the signal processing module, the output end of the signal processing module is connected with the input end of the central control unit, and the output end of the central control unit is connected with the man-machine interface.

[0009] The distributed photovoltaic power station direct current arc on-line monitoring system further improves in that:

[0010] Further, the current sensor and the voltage transformer are arranged at each node of the direct current line in the distributed photovoltaic power station.

[0011] The optical fiber temperature sensor and the magnetic sensor are arranged at the connection part and the weak insulation point prone to arc in the distributed photovoltaic power station.

[0012] Further, the signal processing module includes an analog-to-digital conversion module and a digital filter module, wherein the output ends of the voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are connected with the input end of the central control unit through the analog-to-digital conversion module and the digital filter module.

[0013] The application discloses a kind of distributed photovoltaic power station direct current arc on-line monitoring method, comprising:

[0014] The voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor detect the voltage signal, current signal, temperature signal and magnetic sensitive signal of each monitoring point of the distributed photovoltaic power station.

[0015] The signal processing module pre-processes the voltage signal, current signal, temperature signal and magnetic sensitive signal.

[0016] The central control unit inputs the pre-processed voltage signal, current signal, temperature signal and magnetic sensitive signal into the arc recognition model based on deep learning to determine whether the current distributed photovoltaic power station has direct current arc fault.

[0017] Further, it further includes:

[0018] When the current distributed photovoltaic power station has direct current arc fault, the man-machine interface sends early warning information to the operation and maintenance personnel, and the early warning information includes fault position and fault severity.

[0019] Further, the pre-processing of the voltage signal, the current signal, the temperature signal and the magnetic sensitive signal by the signal processing module includes:

[0020] The voltage signal, the current signal, the temperature signal and the magnetic sensitive signal are subjected to analog-digital conversion and filtering processing.

[0021] Further, the filtering processing is performed by using a finite impulse response filtering algorithm.

[0022] Further, the method further comprises:

[0023] The equipment parameters, the historical monitoring data and the fault records of the distributed photovoltaic power station are stored by using an internal database.

[0024] The distributed photovoltaic power station direct current arc online monitoring method further improves in that:

[0025] The distributed photovoltaic power station direct current arc online monitoring method is implemented by using a computer device, a computer readable storage medium and a computer program.

[0026] The distributed photovoltaic power station direct current arc online monitoring method is implemented by using a computer device, a computer readable storage medium and a computer program.

[0027] The distributed photovoltaic power station direct current arc online monitoring method has the following beneficial effects:

[0028] The distributed photovoltaic power station direct current arc online monitoring system and method effectively solve many problems existing in the direct current arc monitoring of the current distributed photovoltaic power station, and effectively guarantee the safe and stable operation of the power station, so that the direct current arc of the distributed photovoltaic power station is intelligently, accurately and efficiently monitored. BRIEF DESCRIPTION OF DRAWINGS

[0029] The drawings constituting a part of the specification of the present application are used to provide a further understanding of the present application, and the schematic embodiments of the present application and the description thereof are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0030] Figure 1 The system diagram of the present application;

[0031] Figure 2 The method flow chart of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0033] In the description of the present application, it should be understood that the terms "comprising" and "including" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0034] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms, unless the context clearly indicates otherwise.

[0035] It should be further understood that the term "and / or" used in the specification and the appended claims of the present application means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations, for example, A and / or B can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0036] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe the preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range, without departing from the scope of the embodiments of the present application.

[0037] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to the determination" or "in response to the detection." Similarly, the phrase "if determined" or "if detecting (a stated condition or event)" can be interpreted to mean "when determined" or "in response to the determination" or "when detecting (a stated condition or event)" or "in response to the detection (a stated condition or event)," depending on the context.

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0039] The accompanying drawings illustrate various schematic diagrams of structures according to embodiments disclosed herein. These figures are not drawn to scale; for clarity, some details are exaggerated and some details may be omitted. The shapes of the various regions and layers shown in the figures, as well as their relative sizes and positional relationships, are merely exemplary and may deviate in practice due to manufacturing tolerances or technical limitations. Those skilled in the art may design regions / layers with different shapes, sizes, and relative positions as needed.

[0040] Example 1

[0041] refer to Figure 1 The distributed photovoltaic power station DC arc online monitoring system of the present invention comprises the following steps:

[0042] 1) Deployment of sensor units;

[0043] Current sensors and voltage transformers are deployed at various nodes along the DC lines of distributed photovoltaic power plants. For example, high-precision Hall-effect current sensors are installed at the output of PV panel strings, the DC input of combiner boxes, and the DC side of inverters. Taking the ACS712 Hall-effect current sensor as an example, its range can be selected based on the actual current level, such as 5A-30A, with a measurement accuracy of ±1.5%, enabling precise capture of even the smallest changes in DC current with milliampere resolution. For voltage monitoring, LEM series voltage transformers are used, offering an accuracy of ±0.5%, enabling real-time sensing of DC voltage fluctuations.

[0044] Additional fiber optic temperature sensors and magnetic sensors are deployed near arc-prone connections and insulation weaknesses. Fiber optic temperature sensors, with a temperature measurement accuracy of ±0.5°C, are extremely sensitive to local temperature rises and can quickly provide feedback on heat changes caused by arcing. Magnetic sensors, such as the HMC series, use the giant magnetoresistance effect and can sensitively detect magnetic field distortion caused by DC arcing, with nanotesla-level measurement accuracy.

[0045] 2) Constructing signal processing module;

[0046] Field programmable gate array (FPGA) is used as the core processing device, which has high-speed parallel processing capability and can meet the real-time processing demand of massive sensor data. Connected with the sensing unit, it receives analog signals from different sensors. First, the built-in 12-bit ADC (analog-to-digital converter) is used to convert the analog signal into digital signal, and the sampling frequency is set to 10 kHz to ensure that no key information is lost.

[0047] The digital signal enters the digital filter module written by hardware description language (VHDL), which uses finite impulse response (FIR) filtering algorithm to remove noise components such as electromagnetic interference in industrial field according to pre-set filter coefficients, such as coefficients designed by Hamming window function, and restores the true signal waveform.

[0048] 3) Configuring central control unit;

[0049] High-performance industrial control computer is selected, which is equipped with multi-core processor (such as Intel Core i7 series) and runs monitoring software developed based on Windows operating system. The software communicates with the signal processing module through Ethernet, receives processed signal data, and analyzes and judges according to the predetermined logic rules and intelligent algorithms.

[0050] The built-in database is used to store power plant equipment parameters, historical monitoring data, fault records and other information, which is convenient for querying at any time and provides data support for fault diagnosis.

[0051] 4) Designing human-computer interaction interface;

[0052] The human-computer interaction interface based on Web is developed, and operation and maintenance personnel can access it through computer, tablet and other terminal devices using browser. The interface uses intuitive graphical design to display the data collected by each sensor, signal processing results and overall safety evaluation level of the power plant in the form of charts and curves in real time.

[0053] Parameter setting function is provided, and operation and maintenance personnel can adjust filter parameters, warning threshold, sampling frequency and other parameters according to the actual operation of the power plant to ensure the adaptability and flexibility of the system.

[0054] Example two

[0055] Reference Figure 2 The distributed photovoltaic power station direct current arc online monitoring method described in the application comprises the following steps:

[0056] 1) Data acquisition and preliminary processing;

[0057] The sensing unit synchronously collects parameter data such as current, voltage, temperature and magnetic field according to a set sampling period, and transmits the data to the signal processing module. The collected current data sequence is denoted as I(n), the voltage data sequence is denoted as V(n), the temperature data sequence is denoted as T(n), and the magnetic field data sequence is denoted as B(n), where n represents the sampling point sequence number.

[0058] The signal processing module performs denoising processing on each data sequence, and calculates the current change rate ΔI(n) and the voltage fluctuation coefficient K V (n).

[0059] ΔI(n) = I(n) - I(n-1)

[0060] The voltage fluctuation coefficient K V (n) is:

[0061]

[0062] wherein, represents the average value of voltage of the past m sampling points, and m can be set according to actual conditions, for example, m = 10.

[0063] 2) Arc feature extraction and identification;

[0064] The preliminarily processed data are sent into an arc identification model based on deep learning. The model adopts a convolutional neural network (CNN) architecture, and is pre-trained using a large amount of simulation data containing DC arc faults and normal operating states and part of field measured data. The input data are multi-channel data, including current change rate, voltage fluctuation coefficient, temperature change trend and magnetic field distortion features, etc.

[0065] The CNN model automatically extracts deep arc features in the data through multiple convolution layers, pooling layers and fully connected layers. For example, the convolution kernel size of the convolution layer is 3x3, and the step is 1, and local features are extracted through convolution operation; the pooling layer adopts maximum pooling with a window size of 2x2, which is used to reduce the data dimension and improve the calculation efficiency. After the model processing, a probability value P between 0 and 1 is output, which represents the possibility of the current state being a DC arc fault. When P > 0.8 (the threshold value can be adjusted according to actual verification results), it is determined as a suspected DC arc fault.

[0066] 3) Fault diagnosis and early warning;

[0067] After receiving the suspected fault signal, the central control unit further diagnoses by comprehensively considering the multi-sensor data and the current operation condition of the power station. By comparing with the historical normal operation data, it checks whether there is a fault mode matching the current abnormal data. For example, if a slight current mutation, an increased voltage fluctuation, a local temperature rise, and a magnetic field distortion occur at the same time, combined with similar fault cases in the database, it is basically diagnosed as a direct current arc fault.

[0068] Once diagnosed, the central control unit immediately sends a warning message to the operation and maintenance personnel through the human-computer interaction interface, which includes the fault location and the fault severity. At the same time, according to the preset control strategy, it automatically controls the action of the related protection device, such as cutting off the direct current contactor of the fault line, to prevent the arc from expanding and causing a fire or damaging the equipment.

[0069] Embodiment Three

[0070] A distributed photovoltaic power station with an installed capacity of 3 MW is selected as an embodiment, which includes 1500 photovoltaic modules, divided into 50 groups, and connected to 5 inverters through 10 combiner boxes.

[0071] During the two-month test run, the sensor unit accumulatively collected more than 5 million groups of data. Through the present application, 6 direct current arc events were successfully detected. Among them, 3 were caused by loose connection of photovoltaic modules. In the early stage of the arc, the average current change rate reached 0.5 A / s, the voltage fluctuation coefficient increased to 0.15 at most, the temperature near the fault point increased by 15℃ within 5 minutes, the magnetic field distortion exceeded the normal range by 200nT, and the monitoring system issued a warning message within 10 seconds. Another 2 were caused by insulation aging in the combiner box. The current mutation, voltage fluctuation, and other characteristics were also captured in time, and the average warning time was 8 seconds. The last one was an arc fault on the direct current side of the inverter, and the system also responded quickly, warning 12 seconds in advance.

[0072] Through actual verification, the present application can accurately and quickly monitor the direct current arc fault in a complex power station environment, effectively ensure the safe and stable operation of the distributed photovoltaic power station, and greatly reduce the risk of equipment damage and power generation loss caused by direct current arc.

[0073] Embodiment Four

[0074] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for monitoring direct-current arc of distributed photovoltaic power station online when executing the computer program, for example, comprising: detecting voltage signals, current signals, temperature signals, and magnetic sensitive signals of each monitoring point of the distributed photovoltaic power station through a voltage transformer, a current sensor, an optical fiber temperature sensor, and a magnetic sensitive sensor; pre-processing the voltage signals, the current signals, the temperature signals, and the magnetic sensitive signals through a signal processing module; inputting the pre-processed voltage signals, the current signals, the temperature signals, and the magnetic sensitive signals into an arc recognition model based on deep learning through a central control unit to determine whether a direct-current arc fault occurs in the current distributed photovoltaic power station. The memory can include an internal memory, for example, a high-speed random memory, and can also include a non-volatile memory, for example, at least one disk memory, etc.; the processor, the network interface, and the memory are connected to each other through an internal bus, which can be an industry standard architecture bus, a peripheral component interconnect standard bus, an extended industry standard structure bus, etc., and the bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs, specifically, the programs can include program codes, and the program codes include computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data to the processor.

[0075] Embodiment five

[0076] A computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the steps of the method for monitoring direct-current arc of distributed photovoltaic power station online, for example, comprising: detecting voltage signals, current signals, temperature signals, and magnetic sensitive signals of each monitoring point of the distributed photovoltaic power station through a voltage transformer, a current sensor, an optical fiber temperature sensor, and a magnetic sensitive sensor; pre-processing the voltage signals, the current signals, the temperature signals, and the magnetic sensitive signals through a signal processing module; inputting the pre-processed voltage signals, the current signals, the temperature signals, and the magnetic sensitive signals into an arc recognition model based on deep learning through a central control unit to determine whether a direct-current arc fault occurs in the current distributed photovoltaic power station. Specifically, the computer readable storage medium includes but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory can include a random access memory (RAM) and / or a cache memory, etc. The non-volatile memory can include a read-only memory (ROM), a hard disk, a flash memory, an optical disk, a magnetic disk, etc.

[0077] Those skilled in the art will appreciate that embodiments of the application can be readily used as software, hardware, or a combination of software and hardware. In one

[0078] The present application is described in reference to the drawings using a flowchart and / or a block diagram of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart and / or block diagram, and combinations of blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processing system 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 and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0079] These computer program instructions can 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 instructions which implement the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0080] These computer program instructions can 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 flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0081] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0082] It should be understood that the application is not limited to the precise construction which has been described above and illustrated in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application should only be limited by the appended claims.

[0083] The above description is only the preferred embodiment of the present application, not any limitation to the present application, any simple modification, change and equivalent structure change to the above embodiment according to the technical essence of the present application are still within the protection scope of the present application technical solution.

Claims

1. A distributed photovoltaic power station DC arc online monitoring system, characterized in that: Including voltage transformer, current sensor, optical fiber temperature sensor, magnetic sensor, signal processing module, central control unit and human-computer interaction interface; The voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are installed at the monitoring position of the distributed photovoltaic power station. The output ends of the voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are connected to the input end of the signal processing module, the output end of the signal processing module is connected to the input end of the central control unit, and the output end of the central control unit is connected to the human-computer interaction interface.

2. The distributed photovoltaic power station DC arc online monitoring system according to claim 1, characterized in that: Current sensors and voltage transformers are arranged at each node of the DC line in the distributed photovoltaic power station; Optical fiber temperature sensors and magnetic sensors are arranged at connection locations and insulation weak points in distributed photovoltaic power stations where arcs are likely to occur.

3. The distributed photovoltaic power station DC arc online monitoring system according to claim 1, characterized in that: The signal processing module includes an analog-to-digital conversion module and a digital filtering module, wherein the output ends of the voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor are connected to the input end of the central control unit via the analog-to-digital conversion module and the digital filtering module.

4. A method for online monitoring of DC arc in a distributed photovoltaic power station, characterized in that: include: The voltage signal, current signal, temperature signal and magnetic signal of each monitoring point of the distributed photovoltaic power station are detected by voltage transformer, current sensor, optical fiber temperature sensor and magnetic sensor; Preprocessing the voltage signal, current signal, temperature signal and magnetic sensitivity signal through a signal processing module; The pre-processed voltage signal, current signal, temperature signal and magnetic sensitivity signal are input into the arc recognition model based on deep learning through the central control unit to determine whether a DC arc fault occurs in the current distributed photovoltaic power station.

5. The method for online monitoring of DC arc in a distributed photovoltaic power station according to claim 4, characterized in that: Also includes: When a DC arc fault occurs in the current distributed photovoltaic power station, an early warning message is sent to the operation and maintenance personnel through the human-computer interaction interface. The early warning information includes the fault location and fault severity.

6. The method for online monitoring of DC arc in a distributed photovoltaic power station according to claim 4, characterized in that: The process of pre-processing the voltage signal, current signal, temperature signal and magnetic sensitivity signal by the signal processing module is as follows: The voltage signal, current signal, temperature signal and magnetic sensitive signal are subjected to analog-to-digital conversion and filtering processing.

7. The method for online monitoring of DC arc in a distributed photovoltaic power station according to claim 4, characterized in that: Finite impulse response filtering algorithm is used for filtering.

8. The method for online monitoring of DC arc in a distributed photovoltaic power station according to claim 4, characterized in that: Also includes: The built-in database stores equipment parameters, historical monitoring data and fault records of distributed photovoltaic power plants.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for online monitoring of DC arc in a distributed photovoltaic power station as described in any one of claims 4 to 8 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for online monitoring of DC arc in a distributed photovoltaic power station as claimed in any one of claims 4 to 8 are implemented.

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