WO2023120977A1

WO2023120977A1 - Method and system for examining solar photovoltaic power station using unmanned aerial vehicle

Info

Publication number: WO2023120977A1
Application number: PCT/KR2022/017661
Authority: WO
Inventors: 김용수; 최훈주
Original assignee: 주식회사 에스테코
Priority date: 2021-12-21
Filing date: 2022-11-10
Publication date: 2023-06-29
Also published as: KR102454726B1

Abstract

The present invention relates to a method and system for examining a solar photovoltaic power station using an unmanned aerial vehicle, the method comprising: a step in which a monitoring device identifies the positions of a plurality of solar modules and assigns unique numbers to the plurality of solar modules; a step in which at least one first solar module, from among the plurality of solar modules, transmits an abnormal signal to the unmanned aerial vehicle; a step in which the unmanned aerial vehicle captures video data while moving to the position of the at least one first solar module and transmits the video data to the monitoring device; and a step in which the monitoring device analyzes the video data and outputs a monitoring result. Other embodiments are also applicable.

Description

Method and system for diagnosing solar power plant using unmanned air vehicle

The present invention relates to a method and system for diagnosing a solar power plant using an unmanned aerial vehicle.

As problems such as the depletion of natural resources and the environment and safety of thermal and nuclear power generation occur, interest in new and renewable energy is increasing worldwide. Photovoltaic power generation is a new and renewable energy with the most active supply and spread, and its safety and profitability have already been verified, so large-scale photovoltaic power plants are gradually increasing.

Since the maintenance of such a solar power plant is directly related to the amount of energy generated, a lot of time and human resources are invested for maintenance, and research and development for diagnosing solar modules are being actively conducted. In particular, as unmanned aerial vehicles, such as drones, have recently become common, a thermal imaging camera is mounted on the drone to take a thermal image of the surface of the photovoltaic module to detect and manage defects in the photovoltaic module.

In particular, when a situation arises in diagnosing a solar module of a solar power plant installed in a tall building or in a forest where human access is not easy, or diagnosing a solar module at night, no matter how skilled a drone expert is, the surrounding situation It is difficult to clearly check the drone, and it is not easy to adjust the drone.

Embodiments of the present invention to solve these conventional problems are a method and system for diagnosing a solar power plant using an unmanned aerial vehicle capable of preferentially monitoring a photovoltaic module in which an abnormality is detected through communication with a group or individual photovoltaic module. is to provide

A method for diagnosing a photovoltaic power plant using an unmanned aerial vehicle according to an embodiment of the present invention includes the steps of determining, by a monitoring device, the location of a plurality of photovoltaic modules and allocating a unique number to the plurality of photovoltaic modules; Transmitting, by at least one faulty module among the modules, an abnormal signal to the unmanned aerial vehicle, the unmanned aerial vehicle moving to the position of the at least one faulty module and transmitting captured image data to the monitoring device, and the monitoring device It characterized in that it comprises the step of outputting a monitoring result by analyzing the image data.

In addition, the step of allocating a unique number is characterized in that the monitoring device is a step of allocating the unique number to each of the plurality of photovoltaic modules.

In addition, the step of allocating a unique number is characterized in that the step of grouping the plurality of photovoltaic modules by the monitoring device and allocating the unique number to each group.

In addition, the step of transmitting the abnormal signal to the unmanned aerial vehicle includes the step of detecting whether the at least one abnormal module is abnormal, and the at least one abnormal module generating the abnormal signal including the unique number and transmitting the abnormal signal to the unmanned aerial vehicle. It is characterized in that it includes the step of doing.

In addition, the transmitting to the monitoring device may include capturing image data of the at least one abnormal module while the unmanned aerial vehicle moves to the shortest distance between the at least one abnormal module set based on a predetermined movement path, and monitoring the monitoring. characterized in that it is the step of transmitting to the device.

In addition, after the transmitting to the monitoring device, the at least one abnormal module terminates the transmission of the abnormal signal and the unmanned aerial vehicle returns to the starting point to capture image data for the at least one abnormal module. Characterized in that it further comprises the step of terminating.

In addition, the photovoltaic power plant diagnosis system using an unmanned aerial vehicle according to an embodiment of the present invention includes a plurality of photovoltaic modules that generate and transmit an abnormality signal when an abnormality is detected, and the plurality of solar modules that receive the abnormality signal. Of the unmanned air vehicle that moves to the position of at least one abnormal module corresponding to the abnormal signal and captures image data, the locations of the plurality of solar modules are identified, and a unique number is assigned to the plurality of solar modules. It is characterized in that it includes a monitoring device that analyzes the image data received from the unmanned aerial vehicle and outputs a monitoring result.

In addition, the monitoring device may allocate the unique number to each of the plurality of photovoltaic modules or group the plurality of photovoltaic modules and allocate the unique number to each group.

In addition, the abnormal signal may include the unique number of the at least one abnormal module in which the abnormality is detected.

In addition, the unmanned aerial vehicle is characterized in that the video data for the at least one abnormal module is photographed and transmitted to the monitoring device while moving at the shortest distance between the at least one abnormal module set based on a predetermined movement path. .

In addition, the unmanned aerial vehicle is guided to the abnormal solar module based on the abnormal signal and selectively photographs the abnormal solar module, automatically at night without the user's drone control or awareness of the terrain around the power plant. It is characterized in that EL (electro luminance) shooting for the photovoltaic module is possible.

As described above, the photovoltaic power plant diagnosis method and system using an unmanned aerial vehicle according to the present invention diagnoses anomaly of a photovoltaic module by preferentially monitoring the photovoltaic module in which anomaly is detected through communication with a group or individual photovoltaic module. It has the effect of minimizing the amount of time consumed in the city.

In addition, according to the present invention, according to the use of the abnormal signal, there is an effect of selectively photographing only the solar module by automatically guiding the drone to the solar module in which the abnormality occurs without user control of the drone.

In addition, according to the present invention, as the drone is guided based on the abnormal signal, EL (electro luminance) shooting of the drone for the solar module that can be filmed only at night can be performed without a skilled user's drone adjustment and clear recognition of the terrain around the power plant. There is an effect that can be easily performed automatically.

1 is a diagram schematically showing a solar power plant diagnosis system according to an embodiment of the present invention.

2 is a diagram showing a schematic configuration of a solar module according to an embodiment of the present invention.

3 is a diagram showing a schematic configuration of a monitoring device according to an embodiment of the present invention.

4 is a flowchart illustrating a method for diagnosing a solar power plant using an unmanned aerial vehicle according to an embodiment of the present invention.

5 shows the movement sequence of an unmanned aerial vehicle for inspection of a general solar power plant. It is an exemplary diagram for explaining the method for explanation.

6 is an exemplary diagram for explaining a method for explaining a movement sequence of an unmanned aerial vehicle according to an embodiment of the present invention.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings. The detailed description set forth below in conjunction with the accompanying drawings is intended to describe exemplary embodiments of the present invention and is not intended to represent the only embodiments in which the present invention may be practiced. In order to clearly describe the present invention in the drawings, parts irrelevant to the description may be omitted, and the same reference numerals may be used for the same or similar components throughout the specification.

Referring to FIG. 1 , a diagnosis system 10 according to the present invention may include an unmanned aerial vehicle 100, a solar module 200, and a monitoring device 300.

The unmanned aerial vehicle 100 is a device such as a drone, and performs wireless communication with the photovoltaic module 200 and the monitoring device 300 (hereinafter, the unmanned aerial vehicle 100 is also referred to as “drone 100”). In addition, the drone 100 may perform an operation by a controller (not shown) that controls the drone 100, but in the embodiment of the present invention, the operation performed by the monitoring device 300 will be described as an example. do. To this end, the drone 100 uses ^5th generation communication (5G), long term evolution (LTE), long term evolution-advanced (LTE-A), wireless fidelity (Wi-Fi), long range (LoRa), etc. of wireless communication, and global positioning system (GPS) communication with satellites.

In addition, the drone 100 receives an abnormal signal from the solar module 200 and moves to a position of the solar module 200 corresponding to the abnormal signal. At this time, the abnormal signal is a wireless signal such as RF, and may be a signal for inducing the drone 100 (ie, a drone induction signal). For example, a specific photovoltaic module 200 having an abnormality may generate an abnormal signal, and the drone 100 receiving the abnormal signal may be guided to the corresponding solar module 200 according to the abnormal signal. . In addition, identification information (ie, a unique number) of the photovoltaic module 200 that generated the abnormal signal may be included in the abnormal signal.

The drone 100 acquires image data of the photovoltaic module 200 corresponding to the corresponding location and transmits it to the monitoring device 300. To this end, the drone 100 may include an image capturing device such as a camera (not shown) for capturing electro luminance (EL).

The photovoltaic module 200 determines whether there is an abnormality by itself, and the solar module that detects the abnormality (ie, the abnormal module) generates an abnormality signal by itself. An abnormal signal of such an RF wireless signal is a signal completely different from a GPS signal, and may be a signal used in a completely different way.

That is, in the case of using a GPS signal, a device receiving each GPS signal generated by at least three GPS satellites uses a mathematical technique such as a triangulation principle for each corresponding GPS signal to determine its position (i.e., latitude and longitude position). ) is used.

On the other hand, the present invention proposes a method using an abnormal signal, which is a different kind from the GPS signal, without using the GPS signal. That is, the abnormal signal generated by the abnormal module itself is a guiding signal for inducing the drone 100 by the abnormal module, and is an RF wireless signal. At this time, the drone 100 receiving the abnormal signal can determine the abnormal module that generated the abnormal signal (wireless signal) according to the abnormal signal, and even if there is no GPS signal, the location of the abnormal module according to the strength of the abnormal signal. can be induced by For example, if the abnormal signal is large, it may be determined that the drone 100 is located close to the abnormal module, and if the abnormal signal is small, it may be determined that the drone 100 is located far from the abnormal module. , The drone 100 can be guided to the corresponding abnormal module by using the received RF wireless signal characteristics of the abnormal signal.

By using such an abnormal signal, the drone 100 is guided to the abnormal module according to the received abnormal signal and can selectively photograph the abnormal module, and the shortest distance between the abnormal modules set based on the predetermined movement path. The abnormal module can be photographed while moving on the street, and in particular, EL (electro luminance) photographing of the abnormal module can be performed automatically at night without the user's drone control or awareness of the terrain around the power plant. These technical features correspond to features that cannot be implemented in the case of using a GPS signal.

The photovoltaic module 200 includes a first photovoltaic module 200_1, a second photovoltaic module 200_2 to an nth photovoltaic module 200_n, and means a module installed in a photovoltaic power plant. The photovoltaic module 200 may determine whether or not there is an abnormality on its own, and when an abnormality is detected, an abnormality signal capable of calling the drone 100 may be generated and transmitted to the drone 100 . The main operation of the photovoltaic module 200 will be described with reference to FIG. 2 below. 2 is a diagram showing a schematic configuration of a solar module according to an embodiment of the present invention.

Referring to FIG. 2 , the solar module 200 according to the present invention may include a module communication unit 210 , a module sensor unit 220 , a module memory 230 and a module control unit 240 .

The module communication unit 210 may transmit an abnormal signal, which is a drone guidance signal, to the drone 100 . For example, the module communication unit 210 communicates with the drone 100 5 ^th generation communication (5G), long term evolution (LTE), long term evolution-advanced (LTE-A), wireless fidelity (Wi-Fi), LoRa ), etc., global positioning system (GPS) communication with satellites, and other wireless communication based on RF signals.

In addition, in the embodiment of the present invention, the module communication unit 210 is included in the solar module 200 as an example, but is not necessarily limited thereto, and is implemented as a detachable solar module 200 when necessary. may be detached from. In this case, the module communication unit 210 is attached to the photovoltaic module 200 when diagnosis of the photovoltaic power plant is required, and can be removed from the photovoltaic module 200 after the diagnosis of the photovoltaic power plant is completed.

The module sensor unit 220 may include a temperature sensor, a voltage sensor, a current sensor, and a solar radiation sensor. The module sensor unit 220 measures sensing data including temperature, voltage, current, and solar radiation of the photovoltaic module 200 in real time or periodically and provides the measured data to the module control unit 240 .

Of course, the module sensor unit 220 may be implemented as a detachable type and detachable from the solar module 200 when necessary. In this case, the module sensor unit 220 is attached to the photovoltaic module 200 along with the module communication unit 210 when diagnosis of the photovoltaic power plant is required, and after the diagnosis of the photovoltaic power plant is completed, the photovoltaic module 200 ) can be removed from

In addition, the module sensor unit 220 and the module communication unit 210 are implemented as one device and can be attached to and detached from the solar module 200 when necessary.

In the case of adopting the detachable method described above, the inspector of the power plant diagnosis can carry the module communication unit 210 and perform the diagnosis by using it for the power plant requiring diagnosis. In addition, the corresponding module communication unit 210 can be retrieved for the power plant that has been diagnosed. Accordingly, there is an advantage in that the efficiency of power plant diagnosis can be increased and the cost of maintenance of power plant facilities can be reduced.

The module memory 230 may store a unique number assigned by the monitoring device 300 . At this time, the module memory 230 may map and store location information of the photovoltaic module 200 , a unique number, and an ID of the photovoltaic module 200 . A program capable of detecting an abnormality of the photovoltaic module 200 based on the sensing data acquired by the module sensor unit 220 may be stored.

The module control unit 240 detects whether or not the solar module 200 is abnormal based on the sensing data provided from the module sensor unit 220 . At this time, if the sensing data is out of the normal range, the module control unit 240 can confirm that an abnormality has occurred in the photovoltaic module 200, generate an abnormal signal, and transmit it to the drone 100 through the module communication unit 210. . In addition, the module control unit 240 may transmit the abnormal signal and terminate transmission of the abnormal signal when a threshold time elapses.

Although not shown, the solar module 200 may include a display unit such as an LED. Through this, the drone 100 can more accurately check the position of the solar module 200 by simultaneously using the light emitted from the solar module 200 and the abnormal signal.

The monitoring device 300 assigns a unique number to each of the individual photovoltaic modules 200_1, 200_2, ... 200_n constituting the photovoltaic module 200, or groups the photovoltaic modules 200 and assigns a unique number to each group. do. The monitoring device 300 may check the monitoring result of the solar module 200 by analyzing image data of the solar module 200 received from the drone 100 . The main operation of the monitoring device 300 will be described in more detail with reference to FIG. 3 below. 3 is a diagram showing a schematic configuration of a monitoring device according to an embodiment of the present invention.

Referring to FIG. 3 , the monitoring device 300 according to the present invention may include a device communication unit 310, a device input unit 320, a device display unit 330, a device memory 340, and a device control unit 350. .

The device communication unit 310 communicates with the drone 100. The device communication unit 310 transmits a photographing signal for photographing the plurality of solar modules 200 to the drone 100 and receives image data for the solar module 200 from the drone 100 . To this end, the device communication unit 310 communicates with the drone 100 ^5th generation communication (5G), long term evolution (LTE), long term evolution-advanced (LTE-A), wireless fidelity (Wi-Fi), LoRa ( LoRa) and the like can perform wireless communication.

The device input unit 320 generates input data in response to a user input of the monitoring device 300 . To this end, the device input unit 320 may include input devices such as a mouse, a keypad, a dome switch, a touch panel, touch keys and buttons rather than keys.

The device display unit 330 outputs output data according to the operation of the monitoring device 300 . To this end, the device display unit 330 may include a display device such as a liquid crystal display (LCD), a light emitting diode (LED) display, or an organic LED (OLED) display. In addition, the device display unit 330 may be combined with the device input unit 320 and implemented in the form of a touch screen.

The device memory 340 stores a program for allocating a unique number to a plurality of photovoltaic modules 200, a unique number assigned to the photovoltaic module 200, an ID of the photovoltaic module 200, and a photovoltaic module. Information including location information of (200) is mapped and stored. The device memory 340 may store a program capable of analyzing the state of the solar module 200 by analyzing image data of the solar module 200 received from the drone 100 .

The device controller 350 checks the locations of the plurality of photovoltaic modules 200 and allocates unique numbers to the plurality of photovoltaic modules 200 . The device controller 350 analyzes the image data of the photovoltaic module 200 received from the drone 100 and outputs a monitoring result. The device controller 350 may check map data of an area where the solar module 200 is installed in order to determine the location of the solar module 200 . The device controller 350 may select a location where each photovoltaic module 200 is installed using map data, and may check location information about the selected location, for example, GPS information. In addition, the device control unit 350 may check location information of the solar module 200 confirmed by the module communication unit 210 included in the solar module 200 through communication with an artificial satellite.

More specifically, the device controller 350 checks the location of the photovoltaic module 200 installed in the photovoltaic power plant and allocates a unique number to the photovoltaic module 200 based on the confirmed location of the photovoltaic module 200. do. For example, when each of the photovoltaic modules 200 includes the module communication unit 210, the device control unit 350 includes the first photovoltaic module 200_1, the second photovoltaic module 200_2 to the n-th photovoltaic module. Each position of (200_n) may be identified and a unique number may be assigned to each solar module 200.

In addition, when a solar module including the module communication unit 210 exists separately from among the solar modules 200, the device control unit 350 may group the solar module including the module communication unit 210 without fail. there is. For example, if the module communication unit 210 exists only in the first solar module 200_1 in a state where the first solar module 200_1 and the second solar module 200_2 are adjacent to each other, the monitoring device 300 may operate on the first solar module 200_2. The optical module 200_1 and the second photovoltaic module 200_2 may be set as a first group, and a unique number may be assigned to the first group. However, in the embodiment of the present invention, for convenience of description, an example in which a unique number is assigned to each photovoltaic module 200 will be described.

When the assignment of the unique number is completed, the device controller 350 maps information such as the ID of the photovoltaic module 200, the location of the photovoltaic module 200 and the unique number assigned to the photovoltaic module 200 to the device memory. Save to (340). The device controller 350 transmits a unique number assigned to each photovoltaic module 200 to the photovoltaic module 200 and transmits a photographing signal for the photovoltaic module 200 to the drone 100 .

Next, the device controller 350 may analyze the image data of the photovoltaic module 200 received from the drone 100 and display the monitoring result of the photovoltaic module 200 on the device display unit 330 . At this time, the image data received from the drone 100 may be image data for at least one photovoltaic module that transmits an abnormal signal from the photovoltaic module 200 to the drone 100, and the image data includes image data and It may contain a unique number for the solar module it relates to.

Through this, in the present invention, the user for diagnosing the solar power plant can move the drone 100 based on the abnormal signal transmitted from the solar module 200 without manipulating the movement of the drone 100 individually. In addition, since the monitoring device 300 can check which photovoltaic module the image data received from the drone 100 belongs to, the user can clearly check the location of the photovoltaic module in which an error has occurred. Therefore, there is an effect that the diagnosis of the photovoltaic module 200 can be performed regardless of the installation position or diagnosis time of the photovoltaic module 200 .

The first embodiment corresponds to an embodiment based on the case where the solar module 200 includes the module sensor unit 220 .

Referring to FIG. 4 , in step 401 , the monitoring device 300 checks the location of the photovoltaic module 200 and performs step 403 . In step 403, the monitoring device 300 allocates a unique number to the photovoltaic module 200 based on the identified location of the photovoltaic module 200. For example, when each of the photovoltaic modules 200 includes the module communication unit 210, the monitoring device 300 includes the first photovoltaic module 200_1, the second photovoltaic module 200_2 to the n-th photovoltaic module. Each position of (200_n) may be identified and a unique number may be assigned to each solar module 200.

In addition, when the photovoltaic module including the module communication unit 210 exists separately among the photovoltaic modules 200, the monitoring device 300 may group the photovoltaic module including the module communication unit 210 without fail. there is. For example, if the module communication unit 210 exists only in the first solar module 200_1 in a state where the first solar module 200_1 and the second solar module 200_2 are adjacent to each other, the monitoring device 300 may operate on the first solar module 200_2. The optical module 200_1 and the second photovoltaic module 200_2 may be set as a first group, and a unique number may be assigned to the first group. However, in FIG. 4, for convenience of description, an example in which a unique number is assigned to each of the photovoltaic modules 200 will be described.

In step 405, the monitoring device 300 may perform step 407 when the allocation of the unique number is completed, and return to step 401 when the allocation of the unique number is not completed to perform

steps

401 and 403 again. In step 407, the monitoring device 300 maps and stores information such as an ID of the photovoltaic module 200, a location of the photovoltaic module 200, and a unique number assigned to the photovoltaic module 200.

In step 409, the monitoring device 300 transmits the unique number assigned to each photovoltaic module 200 to the photovoltaic module 200, and in step 411, the photovoltaic module 200 stores the assigned unique number. Next, in step 413, the monitoring device 300 transmits a photographing signal for the photovoltaic module 200 to the drone 100. The drone 100 moves to the starting point according to the photographing signal received from the monitoring device 300 and prepares to photograph the photovoltaic module 200 .

In step 415, when at least one of the photovoltaic modules 200 detects an abnormality in each module, an abnormality signal is generated and step 417 is performed. In step 417, at least one solar module that generates the abnormal signal transmits the generated abnormal signal to the drone 100. For example, among the photovoltaic modules 200 as shown in FIG. 6, the second photovoltaic module 200_2, the 31st photovoltaic module, the 40th photovoltaic module, the 53rd photovoltaic module, the 79th photovoltaic module, and the 90th photovoltaic module An abnormal signal may be generated in the solar module.

In step 419, the drone 100 checks the location of the photovoltaic modules that have transmitted the abnormal signal based on the received abnormal signal and performs step 421. In step 421, the drone 100 acquires image data for the photovoltaic modules that have transmitted abnormal signals while moving to the confirmed position, and performs step 423. For example, the drone 100 receives abnormal signals from the second photovoltaic module 200_2, the 31st photovoltaic module, the 40th photovoltaic module, the 53rd photovoltaic module, the 79th photovoltaic module, and the 90th photovoltaic module. Since receiving, image data for the corresponding photovoltaic modules is obtained. To this end, the drone 100 may move by setting the shortest distance between the photovoltaic modules that have transmitted the abnormal signal based on a pre-determined movement path.

In step 423, the drone 100 may transmit the obtained image data to the monitoring device 300. At this time, the drone 100 may transmit the unique number of the photovoltaic module together when transmitting image data to the monitoring device 300. Through this, the monitoring device 300 may check the location of the solar module where the error occurs by checking the location information of the solar module mapped to the unique number.

In step 425, the monitoring device 300 analyzes the image data received from the drone 100, and in step 427, the monitoring device 300 may output the analysis result as a monitoring result. At this time, the monitoring result may be any one of attention, warning, and site visit required.

The photovoltaic modules that have transmitted the abnormal signal in step 429 terminate the transmission of the signal when a threshold time elapses based on the time point at which the abnormal signal is transmitted to the drone 100 . When the abnormal signal is not received from the photovoltaic module 200, the drone 100 may confirm that the diagnosis of the photovoltaic module 200 is completed, move to the starting point, land, and turn off the power.

In addition, although steps 413 and 415 are sequentially performed as an example in FIG. 4 , this is for convenience of description and is not necessarily limited thereto. Step 415 may be performed in real time or periodically after a unique number is assigned to the photovoltaic module 200, and step 417 may be performed at the moment the operation of the drone 100 starts.

In addition, although

steps

425, 427, and 429 are also described as being sequentially performed, step 429 may be performed after step 417 has been performed and a threshold time has elapsed.

In addition, in step 421, the drone 100 sequentially acquires image data for the photovoltaic modules that have transmitted the abnormal signal, and communicates with the photovoltaic module for which the image data has been acquired, so that the photovoltaic module responds to the abnormal signal. A signal instructing transmission to end may be transmitted. In this case, unlike the above-described step 429, the photovoltaic module receiving the corresponding command signal ends transmission of the abnormal signal. That is, the abnormal signal may be automatically turned off in the photovoltaic module of the abnormal signal that has been photographed. Accordingly, it is possible to prevent the drone 100 from photographing the photovoltaic module of the previous abnormal signal again, and there is an advantage in that the photovoltaic module of the remaining abnormal signal can be easily photographed. Of course, even in this case, step 429 may be additionally performed.

In the case of the above-described first embodiment, the drone 100 may automatically check only the photovoltaic module 200 having an abnormality. In particular, it is virtually impossible for even a skilled drone operator to safely control a drone when photographing the solar module 200 at night (eg, EL photographing). However, in the case of the above-described first embodiment, since only the photovoltaic module 200 having an abnormality can be photographed based on an abnormal signal, it is possible to automatically and safely photograph even at night.

5 is an exemplary diagram for explaining a method for explaining a moving sequence of an unmanned aerial vehicle for inspection of a general photovoltaic power plant.

The second embodiment corresponds to an embodiment based on a case in which the solar module 200 does not include the module sensor unit 220 .

First, steps 401 to 411 described in the first embodiment are performed in the same way.

Thereafter, the drone 100 acquires image data for the photovoltaic modules 200 to be inspected. That is, the drone 100 may obtain image data for each photovoltaic module while sequentially moving along a predetermined movement path. Of course, the image data at this time is image data for detecting abnormalities in the photovoltaic module 200, and may be approximate image data (eg, low-quality image data, etc.) compared to detailed image data to be described later.

For example, referring to FIG. 5, the drone 100 includes modules 1 to 16, modules 32 to 17, modules 33 to 48, modules 81 to 96, and modules 80 to 65. Image data for each photovoltaic module 100 may be obtained while moving along a predetermined movement path from module No. 49 to module No. 64 as indicated by an arrow.

Thereafter, the drone 100 may transmit the acquired image data to the monitoring device 300. At this time, the drone 100 may transmit the unique number of the photovoltaic module together when transmitting image data to the monitoring device 300. In addition, the monitoring device 300 may analyze the image data received from the drone 100 to derive a photovoltaic module having an abnormality, and transmit a unique number for the derived photovoltaic module to the drone 100. Of course, the drone 100 may analyze the obtained image data on its own without transmitting the image data to the monitoring device 300 to derive a photovoltaic module with an abnormality.

Thereafter, the drone 100 communicates with the photovoltaic module determined to have an abnormality, and transmits a signal instructing the photovoltaic module to generate an abnormality signal. Accordingly, the photovoltaic module receiving the command signal generates an abnormal signal.

Thereafter, contents related to steps 419 to 429 described above in the first embodiment may be performed in the same manner.

In the above-described second embodiment, as in the above-described first embodiment, the drone 100 can automatically check only the photovoltaic module 200 having an abnormality. In particular, it is virtually impossible for even a skilled drone operator to safely control a drone when photographing the solar module 200 at night (eg, EL photographing). However, in the case of the above-described second embodiment, since only the photovoltaic module 200 having an abnormality can be photographed based on an abnormal signal, it is possible to automatically and safely photograph even at night.

On the other hand, the drone 100 in the present invention, as shown in FIG. 6, the modules in which the abnormal signal was generated, for example, the second module, the 31st module, the 40th module, the 90th module, the 79th module, and the 53rd module in order. While moving, it is possible to selectively acquire image data only for the solar module in which an abnormality is detected. To this end, the drone 100 may acquire image data by checking the shortest distance to solar modules in which an abnormal signal is generated based on a previously determined movement path, for example, as shown in FIG. 5 . Through this, since the present invention can acquire image data while moving between the solar modules in which the abnormality is detected by the shortest path, there is an effect of ensuring the minimization of the flight time of the drone 100.

That is, in the prior art, only all photovoltaic modules were photographed as shown in FIG. 5 .

In contrast, the present invention uses a method of inducing the drone 100 to the photovoltaic module with an abnormality based on an abnormal signal, so that the error as shown in FIG. 6 occurs without direct drone control by the user according to the first embodiment. Only generated solar modules can be selectively photographed. Of course, in the case of the second embodiment of the present invention, after all the photovoltaic modules as shown in FIG. 5 are photographed, only the photovoltaic modules in which an error occurs as shown in FIG. 6 can be selectively photographed.

The present invention configured as described above has the advantage of minimizing the time consumed when diagnosing an abnormality of a solar module by preferentially monitoring the photovoltaic module in which an abnormality is detected through communication with a group or individual photovoltaic module. there is In addition, according to the present invention, according to the abnormal signal, there is an advantage that the drone can be automatically guided to the solar module in which the abnormality occurs without user's control of the drone, and only the corresponding solar module can be selectively photographed. In addition, according to the present invention, as the drone is guided based on the abnormal signal, EL (electro luminance) shooting of the drone for the solar module that can be filmed only at night can be performed without a skilled user's drone adjustment and clear recognition of the terrain around the power plant. It has the advantage that it can be done automatically and easily.

Embodiments of the present invention disclosed in the present specification and drawings are only presented as specific examples to easily explain the technical content of the present invention and help understanding of the present invention, and are not intended to limit the scope of the present invention. Therefore, the scope of the present invention should be construed as including all changes or modifications derived based on the technical idea of the present invention in addition to the embodiments disclosed herein.

The present invention relates to a method and system for diagnosing a photovoltaic power plant using an unmanned aerial vehicle, and a photovoltaic power plant using an unmanned air vehicle capable of preferentially monitoring a photovoltaic module in which an abnormality is detected through communication with a group or individual photovoltaic module. Since it can be provided as a diagnostic method and system, there is industrial applicability.

Claims

As a solar power plant diagnosis method for preferentially monitoring an abnormal module, which is a solar module that detects an anomaly,

Step, by a monitoring device, identifying locations of a plurality of photovoltaic modules and allocating unique numbers to the plurality of photovoltaic modules;

At least one abnormal module among the plurality of photovoltaic modules determines whether or not an abnormality is detected by using a module sensor unit including one of a temperature sensor, a current sensor, and a solar radiation sensor. Generating an abnormal signal, which is an induction signal, through a module communication unit, and receiving the generated abnormal signal by an unmanned aerial vehicle;

moving the unmanned aerial vehicle to the location of the at least one abnormal module using the received abnormal signal and transmitting captured image data to the monitoring device; and

Including; analyzing the image data by the monitoring device and outputting a monitoring result;

The abnormal signal is an RF wireless signal for the abnormal module to guide the unmanned aerial vehicle;

In the transmitting step, the unmanned aerial vehicle is guided to the abnormal module according to the received abnormal signal and selectively photographs the abnormal module, while moving to the shortest distance between the abnormal modules set based on a pre-determined movement path. A method for diagnosing a photovoltaic power plant comprising the step of photographing an abnormal module and automatically performing EL (electro luminance) photographing of the abnormal module at night without a user adjusting a drone or recognizing the terrain around the power plant.
According to claim 1,

In the plurality of solar modules, the module communication unit and the module sensor unit are detachably implemented, and when diagnosis of a solar power plant is required, the module communication unit and the module sensor unit are attached to the solar module, and the diagnosis of the solar power plant is performed. A method for diagnosing a solar power plant in which the module communication unit and the module sensor unit are removed from the solar module after the completion.
According to claim 1,

The step of assigning the unique number is,

The step of allocating the unique number to each of the plurality of photovoltaic modules by the monitoring device.
According to claim 1,

The step of assigning the unique number is,

The step of grouping the plurality of photovoltaic modules by the monitoring device and allocating the unique number to each group.
According to claim 1,

After the step of transmitting to the monitoring device,

terminating transmission of the abnormal signal by the at least one abnormal module; and

returning the unmanned aerial vehicle to a starting point and terminating image data capture of the at least one abnormal module;

A method for diagnosing a photovoltaic power plant further comprising a.
A solar power plant diagnosis system for preferentially monitoring an abnormal module, which is a solar module that detects an anomaly,

The module sensor unit including one of a temperature sensor, a current sensor, and a solar radiation sensor is used to determine an abnormality by itself, and when an abnormality is detected, an abnormal signal, a wireless induced signal including its own number, is transmitted through the module communication unit. A plurality of photovoltaic modules generating and transmitting;

When the abnormal signal is received, using the received abnormal signal, an unmanned aerial vehicle moves to a position of at least one module corresponding to the received abnormal signal among the plurality of photovoltaic modules and captures image data; and

A monitoring device that identifies the locations of the plurality of photovoltaic modules, allocates unique numbers to the plurality of photovoltaic modules, analyzes the image data received from the unmanned aerial vehicle, and outputs a monitoring result,

The abnormal signal is an RF wireless signal for the abnormal module to guide the unmanned aerial vehicle;

The unmanned air vehicle is guided to the abnormal module according to the abnormal signal received and selectively photographs the abnormal module, and photographs the abnormal module while moving to the shortest distance between the abnormal modules set based on a predetermined movement path. , Photovoltaic power plant diagnosis system that automatically performs EL (electro luminance) imaging of the abnormal module at night without the user's drone control or awareness of the terrain around the power plant.
According to claim 6,

In the plurality of solar modules, the module communication unit and the module sensor unit are detachably implemented, and when diagnosis of a solar power plant is required, the module communication unit and the module sensor unit are attached to the solar module, and the diagnosis of the solar power plant is performed. The solar power plant diagnosis system in which the module communication unit and the module sensor unit are removed from the solar module after the completion of the module.
According to claim 6,

The monitoring device assigns the unique number to each of the plurality of photovoltaic modules.
According to claim 6,

The monitoring device assigns the unique number to each of the plurality of photovoltaic modules, or groups the plurality of photovoltaic modules and allocates the unique number to each group.
According to claim 6,

After transmitting the video data captured by the unmanned aerial vehicle to the monitoring device, the at least one abnormal module terminates transmission of the abnormal signal, and the unmanned aerial vehicle returns to the starting point, and the at least one abnormal module Photovoltaic power plant diagnosis system that ends the shooting of image data for