Railway long-distance strip-shaped photovoltaic power generation control method, system and device

Abstract

The invention relates to the technical field of new energy power generation, and discloses a railway long-distance strip-shaped photovoltaic power generation control method, system and device, and the method comprises the steps: continuously installing photovoltaic panels between rails to form a photovoltaic power generation system, integrating the photovoltaic power generation system into a strip-shaped photovoltaic power station, and storing the electric power collected by the photovoltaic panels; on the premise that normal operation of a railway is guaranteed, the strip-shaped photovoltaic power stations are connected into a railway power grid system in a distributed mode or consumed in a distributed mode through cables so as to supply power to a railway power grid. A spraying facility is attached to the bottom of a train, a camera is installed in front of the train, through automatic induction and data storage of the spraying facility, spraying behaviors and abnormal data are recorded, when the train passes, whether a photovoltaic panel needs to be cleaned or is abnormal or not is judged in advance, and spraying cleaning or abnormal data feedback of the photovoltaic panel is achieved. The system comprises a photovoltaic power generation module, an electric energy network access module and a cleaning early warning module. According to the invention, utilization of green energy is promoted, and dependence on fossil fuel is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable energy power generation, and in particular to a method, system and device for controlling long-distance strip photovoltaic power generation on railways. Background Art

[0002] At present, the total mileage of railways in my country has reached 159,000 kilometers, and the daily operation of trains requires a large amount of energy supply. At present, photovoltaics are not widely used in the railway industry. Rooftop photovoltaics are installed in some stations and generate power generation benefits. However, within the scope of strip-shaped long-distance railway land, due to the narrow space and limited available space, clean energy has not yet been fully developed and utilized.

[0003] Prior art 1, Chinese patent, application number 202311221474.4 discloses an ecological freight railway photovoltaic power generation system, including a photovoltaic power generation unit, a railway 10KV box-type substation, a railway 10KV substation, a first photovoltaic power generation switch station and a second photovoltaic power generation switch station, the photovoltaic power generation unit includes a station photovoltaic power generation unit and a section line photovoltaic power generation unit, the station photovoltaic power generation unit and the first photovoltaic power generation switch station are arranged at the station, the station photovoltaic power generation unit is used to centrally converge the generated power through the first photovoltaic power generation switch station during the day, and then merge it into the railway 10KV substation, and the railway 10KV substation is used to supply power to the station load of the railway system; the section line photovoltaic power generation unit and the second photovoltaic power generation switch station are arranged on the section line, and the section line photovoltaic power generation unit is used to centrally converge the generated power through the second photovoltaic power generation switch station during the day, and then merge it into the railway 10KV box-type substation, and the railway 10KV box-type substation is used to supply power to the section load of the railway system. Although railway photovoltaic power generation has been achieved, it is only generated at the station, and the space along the railway has not been fully utilized, resulting in a certain degree of resource waste.

[0004] Prior art 2, Chinese patent, application number 202311219010.X discloses a railway photovoltaic power generation grid-connected station access system, including: photovoltaic power generation unit, photovoltaic grid-connected outlet cabinet, photovoltaic grid-connected access cabinet and power grid system; photovoltaic power generation unit is connected to photovoltaic grid-connected access cabinet through photovoltaic grid-connected outlet cabinet, and is connected to railway 10kw substation and power grid system through photovoltaic grid-connected access cabinet, wherein, there is a fault monitoring and intelligent protection system connected between photovoltaic grid-connected outlet cabinet and photovoltaic grid-connected access cabinet, the fault monitoring and intelligent protection system is used to monitor the output power of photovoltaic power generation unit and the load power of railway system, when the output power of photovoltaic power generation unit is greater than the load power of railway system, the surplus power of photovoltaic power generation unit is input into power grid system, and surplus power is connected to the grid, when the output power of photovoltaic power generation unit is less than the load power of railway system, the power grid system is controlled to supply power to railway system. Although the reliability of power supply of railway facilities is guaranteed and photovoltaic power supply of railway slope is realized, it is not used within the scope of internal land use of railway, resulting in waste of resources.

[0005] Prior art three, Chinese patent, application number 202410221873.9 discloses a method for optimizing the configuration of photovoltaic resources along a railway with an energy storage system; the method includes: dividing the various sections of the railway line according to geographic information data, calibrating the slope type of each section, and determining the slope resource coefficient and slope development coefficient of each section: calculating the annual average solar energy resources of each section according to the slope type, slope resource coefficient and slope development coefficient of each section, determining the section for implementing solar energy resource development, calculating the total annual average solar energy resources that can be developed along the line, and constructing a multi-objective configuration function of photovoltaic resources along the railway with energy storage with the goal of minimizing the total cost, solving the multi-objective configuration function through an optimization algorithm, and obtaining an optimal configuration plan for photovoltaic resources along the energy storage system. Although the measurement of scattered photovoltaic resources along long-distance railway lines is realized based on the line data along the railway, it provides statistical tools and guidance plans for photovoltaic development along the railway. However, it requires a higher initial investment, and the grid connection loss is large, which further increases the cost.

[0006] At present, the existing technologies 1, 2 and 3 only generate electricity at the station, and the space along the railway is not fully utilized, resulting in a certain degree of resource waste, requiring a high initial investment, and the grid connection loss is large, further increasing the cost. Therefore, the present invention provides a set of technologies for applying photovoltaic modules to tracks, which can make full use of the area between the rails, continuously form a photovoltaic power generation system, integrate into a strip photovoltaic power station, and access the railway power grid system in a decentralized manner, avoiding problems related to power loss in long-distance transmission, and providing clean energy guarantee for the operation of the railway through decentralized power generation and decentralized consumption. At the same time, the present invention fully considers the safety guarantee of the normal operation of the railway. Summary of the invention

[0007] The main purpose of the present invention is to provide a railway long-distance strip photovoltaic power generation control method, system and device to solve the problem in the prior art that power is only generated at the station, the space along the railway is not fully utilized, resulting in a certain degree of resource waste, requiring a high initial investment, and the grid-connected loss is large, further increasing the cost.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A railway long-distance belt photovoltaic power generation control system, the railway long-distance belt photovoltaic power generation control system comprising:

[0010] Photovoltaic power generation module, used to continuously install photovoltaic panels between rails to form a photovoltaic power generation system, and integrated into a strip photovoltaic power station to store the electricity collected by the photovoltaic panels;

[0011] The power grid access module is used to connect the strip photovoltaic power station to the railway power grid system in a decentralized manner through cables to supply electricity to the railway power grid under the premise of ensuring the normal operation of the railway;

[0012] The cleaning warning module is used to attach the spraying facilities to the bottom of the train, and the camera is installed in front of the vehicle. The spraying behavior and abnormal data are recorded through automatic sensing and data storage of the spraying facilities. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning or abnormal data of the photovoltaic panels are fed back through intelligent control.

[0013] To achieve the above object, the present invention provides the following technical solutions:

[0014] A railway long-distance strip photovoltaic power generation control device, which is applied to the railway long-distance strip photovoltaic power generation control system, the railway long-distance strip photovoltaic power generation control device comprises: a track buckle assembly, a rail, a special-shaped support, a spray device with a memory storage function, a photovoltaic panel, a sleeper, an insulator, an anchor bolt, a buckle assembly, a cantilever steel plate beam, a longitudinal connection clamp, a side anchor, a spring shock absorber, a longitudinal buckle, and a guide rail supporting the photovoltaic panel;

[0015] Among them, the rail is connected to the rail through the track clip assembly under the rail, an insulator is arranged between the clip assembly and the rail, and the clip assembly is connected and fixed by anchor bolts; the cantilevered steel plate beam is extended to form the supporting structure of the photovoltaic module, and is connected to the special-shaped support member on the cantilevered steel plate beam through anchor bolts, and the special-shaped support member is connected to the upper photovoltaic panel through the side anchor member on the side close to the rail, and a spring shock absorber is installed on the opposite side, and a longitudinal connection clamp is installed above the photovoltaic panel where the spring shock absorber is installed; the photovoltaic panel is located above the railway track, and a spray device with a memory storage function is installed on the train above it, and is attached to the train, and the photovoltaic is installed on the guide rail supporting the photovoltaic panel, and the guide rail supporting the photovoltaic panel is fixed by a longitudinal clip;

[0016] The special-shaped support is connected to the cantilevered steel plate beam through anchor bolts, and the upper side of the special-shaped support close to the rail is connected to the upper photovoltaic panel through side anchors. A spring shock absorber is installed on the opposite side, and a longitudinal connecting clamp is installed above the photovoltaic panel at the installation position of the spring shock absorber.

[0017] To achieve the above object, the present invention provides the following technical solutions:

[0018] A railway long-distance strip photovoltaic power generation control method, which is applied to the railway long-distance strip photovoltaic power generation control system, and the railway long-distance strip photovoltaic power generation control method includes:

[0019] Photovoltaic panels are installed continuously between the rails to form a photovoltaic power generation system, which is integrated into a strip photovoltaic power station to store the electricity collected by the photovoltaic panels;

[0020] Under the premise of ensuring the normal operation of the railway, the strip photovoltaic power station is decentralizedly connected to the railway power grid system through cables to supply electricity to the railway power grid;

[0021] The spraying facilities are attached to the bottom of the train, and the camera is installed in front of the vehicle. The spraying behavior and abnormal data are recorded through automatic sensing and data storage of the spraying facilities. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning of the photovoltaic panels or the feedback of abnormal data is realized through intelligent control.

[0022] As a further improvement of the present invention, the control process of the spray facility includes:

[0023] The spraying facilities are attached to the trains and the trains are filled with clean water in the railway maintenance section;

[0024] The spraying facility determines whether the photovoltaic panels need to be cleaned according to the last spraying record provided by the data storage device or whether there is a mandatory cleaning instruction. If cleaning is required, the spraying facility is started; if cleaning is not required, the train leaves normally;

[0025] During the process of cleaning the photovoltaic panels with the spraying facilities, the spraying intensity is adjusted according to the spraying feedback. After the photovoltaic panels are cleaned, the train leaves.

[0026] As a further improvement of the present invention, the process of starting the spray facility includes:

[0027] After the train enters the railway maintenance section and is filled with cleaning water, the spray facility is first initialized; after passing the self-inspection, it enters the standby state; the spray facility obtains the last spray record through the data storage device, or receives a forced cleaning instruction; determines whether the photovoltaic panel needs to be cleaned; if the judgment result is that cleaning is required, it proceeds to the next step; if not, the train leaves normally;

[0028] After determining that cleaning is needed, the spraying facility begins preparation, including turning on the water pump, starting the motor of the spraying device, and adjusting the nozzle angle; at the same time, the initial spraying intensity is preset according to the current state of the photovoltaic panel;

[0029] The spraying facility starts to clean the photovoltaic panels. During the spraying process, the spraying effect is monitored in real time, and the spraying intensity is dynamically adjusted through data fed back by the sensors. When the photovoltaic panels are cleaned, the spraying facility stops spraying, turns off the water pump and motor, and resets all components to their initial state.

[0030] As a further improvement of the present invention, the process of determining whether the photovoltaic panel needs to be cleaned includes:

[0031] Collect a large amount of historical spray records from the database, including the time, amount and effect of each spray; identify the periodicity of photovoltaic panel cleaning through time series analysis;

[0032] Through regression analysis, a relationship model between cleaning cycle and cleaning effect is established to predict the improvement of power generation efficiency after cleaning under different dust accumulation levels; a cleaning demand model is established based on the prediction results;

[0033] Determine whether there is a forced cleaning instruction input. If there is a forced cleaning instruction input, the historical data and the content of the forced cleaning instruction are automatically used to generate a cleaning decision, confirm the cleaning requirement level, and perform spraying; if there is no forced cleaning instruction, the cleaning decision is automatically generated according to the historical data and spraying is performed.

[0034] As a further improvement of the present invention, a process of establishing a cleaning demand model based on the prediction results includes:

[0035] A multi-level trend analysis method is used to identify the long-term, medium-term and short-term trends of photovoltaic panel cleaning demand from historical data, and the seasonal and cyclical patterns of cleaning demand are obtained;

[0036] Polynomial regression is used for modeling. Through a multi-stage training method, coarse-grained training is first performed, followed by fine-grained adjustment, to gradually optimize model parameters. Nested cross-validation is used to evaluate the stability and accuracy of the model.

[0037] Combined with the confidence interval of the Bayesian evaluation prediction results, different thresholds for cleaning demand levels are set according to different cleaning needs; combined with historical data, the prediction results of the regression model and the set thresholds, the optimal cleaning decision is automatically generated;

[0038] The historical data, the prediction results of the regression model and the set threshold are integrated to form a comprehensive data set; the integrated data is analyzed through learning to identify the key factors of cleaning needs, such as cleaning frequency, cleaning effect, and seasonal changes; decision rules are set based on the integrated data and analysis results; when the predicted cleaning demand exceeds the set threshold, a cleaning decision is automatically generated;

[0039] Natural language processing is used to parse the content of the forced cleaning instructions, and the forced cleaning instructions are integrated and verified with historical data. In the case of forced cleaning instructions, the forced cleaning instructions are executed first; and the cleaning decisions are dynamically adjusted according to the content of the forced cleaning instructions and historical data.

[0040] As a further improvement of the present invention, the process of the spraying facility determining whether the photovoltaic panel is abnormal includes:

[0041] The camera is installed in front of the train. After the warning device is activated, the camera starts to capture image data in front of the train.

[0042] The early warning device determines whether there is rockfall damage to the photovoltaic panel, or whether the photovoltaic panel is warped and deformed. If there is rockfall damage to the photovoltaic panel or the photovoltaic panel is warped and deformed, the photovoltaic panel is abnormal;

[0043] If the photovoltaic panel is judged to be abnormal, a warning signal will be sent to the data center to remind relevant staff to take repair measures. If the photovoltaic panel is judged to be normal, the train will pass normally.

[0044] As a further improvement of the present invention, the process of determining whether a photovoltaic panel is abnormal includes:

[0045] A camera is installed in front of the train. After the warning device is activated, the camera starts to capture real-time image data in front of the train. The captured image data is pre-processed, including denoising, contrast enhancement and resolution adjustment.

[0046] Extract the features, shape, color and movement trajectory of the rockfall in the image; compare with the preset track range features, identify the extracted features, and determine whether there is a rockfall; after identifying the rockfall, locate the specific position of the rockfall in the image;

[0047] Extract the features, edges, textures and color distribution of photovoltaic panels from real-time impact data, analyze the features of photovoltaic panels and determine whether there is warping deformation; after identifying the warping deformation, evaluate the degree of deformation and determine whether it reaches the abnormal threshold;

[0048] Combining the results of rockfall detection and photovoltaic panel warping and deformation detection, a comprehensive judgment is made whether there is any abnormality with the photovoltaic panel. If it is judged that the photovoltaic panel is abnormal, a warning signal is generated and sent to the data center through wireless communication technology. After receiving the warning signal, the data center reminds relevant staff to take repair measures. If there is no abnormality, the train passes normally.

[0049] As a further improvement of the present invention, the process of determining whether warping deformation exists includes:

[0050] From the preprocessed image data, the features of the photovoltaic panels are extracted through edge detection algorithm, the texture features are obtained through texture analysis, and the color distribution is analyzed through color histogram;

[0051] Hough transform is used to analyze whether the shape of the photovoltaic panel is deformed; the change in texture features is used to determine whether the photovoltaic panel is warped. Changes in texture uniformity or symmetry may indicate that the photovoltaic panel is warped; changes in color distribution are used to determine whether the photovoltaic panel is warped. Inhomogeneity in color distribution may indicate that the surface of the photovoltaic panel is deformed.

[0052] Calculate the degree of change in the curvature or texture of the edge of the photovoltaic panel to quantify the size of the deformation; compare the quantified deformation degree with the preset abnormal threshold to determine whether the deformation reaches the abnormal threshold; combine the results of rockfall detection and photovoltaic panel warping deformation detection to comprehensively determine whether there is an abnormality in the photovoltaic panel; if the photovoltaic panel is judged to be abnormal, generate a warning signal.

[0053] The present invention effectively utilizes the space resources along the railway by continuously installing photovoltaic panels between the rails, and integrates them into a strip photovoltaic power station, which can efficiently collect, convert and store solar energy, and provide renewable energy for the railway system; it realizes the seamless connection between photovoltaic power and the railway power grid, ensures the stable supply of electricity, and the decentralized access method reduces the impact on the power grid and improves the stability of the power system; it realizes real-time monitoring and intelligent maintenance of photovoltaic panels, improves the power generation efficiency and service life of photovoltaic panels, and can accurately record spraying behavior and abnormal data through automatic sensing and data storage, providing strong support for subsequent maintenance and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a functional module schematic diagram of an embodiment of a railway long-distance strip photovoltaic power generation control system of the present invention;

[0055] Figure 2 This is a functional module schematic diagram of an embodiment of a railway long-distance strip photovoltaic power generation control device of the present invention;

[0056] Figure 3 This is a functional module schematic diagram of a longitudinal buckle and a guide rail supporting a photovoltaic panel in one embodiment of a railway long-distance strip photovoltaic power generation control device of the present invention;

[0057] Figure 4 This is a functional module schematic diagram of a longitudinal connection clamp, a side anchor and a spring shock absorber in one embodiment of a railway long-distance strip photovoltaic power generation control device of the present invention;

[0058] Figure 5 A schematic diagram of the steps of an embodiment of a method for controlling long-distance strip photovoltaic power generation on railways according to the present invention;

[0059] Figure 6 It is a schematic flow chart of the steps of controlling the spraying facilities of one embodiment of the railway long-distance strip photovoltaic power generation control method of the present invention;

[0060] Figure 7 This is a schematic diagram of the control of the spraying facilities of one embodiment of the railway long-distance strip photovoltaic power generation control method of the present invention;

[0061] Figure 8 This is a schematic flow chart of the steps of spraying facilities to determine whether a photovoltaic panel is abnormal in one embodiment of a railway long-distance strip photovoltaic power generation control method of the present invention;

[0062] Fig. 9 This is a schematic diagram of a spray facility in one embodiment of the railway long-distance strip photovoltaic power generation control method of the present invention to determine whether the photovoltaic panel is abnormal;

[0063] Fig.10 It is a structural schematic diagram of an embodiment of an electronic device of the present invention;

[0064] Fig.11 It is a schematic structural diagram of an embodiment of the storage medium of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] The terms "first", "second" and "third" in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" can explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0067] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0068] like Figure 1 As shown, this embodiment provides an embodiment of a railway long-distance strip photovoltaic power generation control system. In this embodiment, the railway long-distance strip photovoltaic power generation control system includes a photovoltaic power generation module, a power grid access module, and a cleaning warning module that are electrically connected in sequence;

[0069] Among them, the photovoltaic power generation module is used to continuously install photovoltaic panels between the rails to form a photovoltaic power generation system, and integrate them into a strip photovoltaic power station to store the electricity collected by the photovoltaic panels; the power grid access module is used to connect the strip photovoltaic power station to the railway power grid system in a decentralized manner through cables on the premise of ensuring the normal operation of the railway to supply electricity to the railway power grid; the cleaning warning module is used to attach the spray facilities to the bottom of the train, and the camera is installed in front of the vehicle. Through the automatic sensing and data storage of the spray facilities, the spray behavior and abnormal data are recorded. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning or abnormal data of the photovoltaic panels are fed back through intelligent control.

[0070] Preferably, the photovoltaic power generation module of this embodiment continuously installs photovoltaic panels between the rails, which can make full use of the space resources along the railway, especially in areas with abundant sunshine. The installation method can maximize the collection of solar energy and be integrated into a strip photovoltaic power station, which can efficiently store the electricity collected by the photovoltaic panels and provide a stable energy source for the power supply; the power access module, on the premise of ensuring the normal operation of the railway, connects the power of the strip photovoltaic power station to the railway power grid system in a decentralized manner through cables, which can ensure the stable supply of electricity. This access method can make full use of the electricity generated by the photovoltaic power station, reduce dependence on the external power grid, and improve the resource self-sufficiency rate of the railway system; the cleaning warning module can realize real-time monitoring and cleaning of the photovoltaic panels by installing spray facilities and cameras on the train. The automatic sensing and data storage functions can judge in advance whether the photovoltaic panels need to be cleaned or are abnormal, thereby realizing intelligent maintenance of the photovoltaic panels.

[0071] In summary, this embodiment helps to promote the use of green energy, reduce dependence on fossil fuels, and reduce carbon emissions. By providing electricity to the railway system, the self-sufficiency of the railway system can be further enhanced and energy security can be improved. By incorporating photovoltaic power into the railway power grid system, diversified energy utilization can be achieved, energy utilization can be improved, and the stability and reliability of the railway system can be enhanced, providing more reliable power guarantee for railway operation. It helps to keep photovoltaic panels clean and operate efficiently, and extend the service life of photovoltaic panels. Through intelligent control and early warning, the operation and maintenance costs of photovoltaic power stations can be reduced, and the overall energy utilization efficiency can be improved.

[0072] Furthermore, the cleaning warning module specifically includes:

[0073] The water supply submodule is used to attach the spraying facilities to the train, and the train is filled with clean water in the railway maintenance section;

[0074] The cleaning judgment submodule is used for the spraying facility to judge whether the photovoltaic panel needs to be cleaned according to the last spraying record provided by the data storage device or whether there is a mandatory cleaning instruction. If cleaning is required, the spraying facility is started; if cleaning is not required, the train leaves normally;

[0075] The intensity adjustment submodule is used to adjust the spray intensity according to the spray feedback during the process of spraying facilities cleaning photovoltaic panels. After the photovoltaic panels are cleaned, the train leaves.

[0076] Preferably, the water supply submodule of this embodiment attaches the spraying facilities to the train, and the train is filled with clean water in the railway maintenance section to ensure that the spraying facilities have sufficient clean water supply; through the preset water supply points, it can be ensured that the spraying facilities always have sufficient water supply during the travel of the train and are ready to clean the photovoltaic panels at any time; the spraying facilities in the cleaning judgment submodule judge whether the photovoltaic panels need to be cleaned according to the last spraying record provided by the data storage device or according to whether there is a forced cleaning instruction. Through data analysis, the cleaning needs of the photovoltaic panels can be accurately judged, unnecessary cleaning operations can be avoided, and water resources and energy can be saved; in the intensity adjustment submodule, during the process of cleaning the photovoltaic panels with the spraying facilities, the spraying intensity is adjusted according to the spraying feedback, which ensures the cleaning effect while avoiding damage to the photovoltaic panels caused by excessive cleaning. After the cleaning is completed, the train leaves, realizing the automation and intelligence of the cleaning work.

[0077] To sum up, this embodiment ensures the continuous working capability of the spraying facilities, avoids the interruption of cleaning work due to insufficient water source, improves the efficiency and reliability of photovoltaic panel cleaning work, and helps to maintain the cleanliness and power generation efficiency of photovoltaic panels; realizes the intelligence and automation of photovoltaic panel cleaning work, improves the accuracy and efficiency of cleaning work, reduces unnecessary cleaning operations, extends the service life of photovoltaic panels, and reduces operation and maintenance costs; improves the intelligence level of photovoltaic panel cleaning work, ensures the cleaning effect, and protects the service life of photovoltaic panels, realizes the automation of cleaning work, reduces manual intervention, and improves work efficiency and safety.

[0078] Furthermore, the cleaning warning module specifically includes:

[0079] The image acquisition submodule installs a camera in front of the train. After the warning device is activated, the camera starts to capture image data in front of the train.

[0080] The abnormality judgment submodule, the early warning device judges whether there is rockfall damage to the photovoltaic panel, or whether the photovoltaic panel is warped and deformed, and judges whether there is an abnormality in the photovoltaic panel. If there is rockfall damage to the photovoltaic panel or the photovoltaic panel is warped and deformed, the photovoltaic panel is abnormal;

[0081] The warning submodule sends a warning signal to the data center if it is judged that the photovoltaic panel is abnormal, so as to remind the relevant staff to take repair measures. If it is judged that there is no abnormality in the photovoltaic panel, the train passes normally.

[0082] Preferably, the image acquisition submodule of this embodiment installs a camera in front of the train to capture image data in front of the train. When the early warning device is activated, the camera starts working immediately to record the image information in front of the train in real time. The abnormality judgment submodule uses advanced image processing and recognition technology to process and analyze the image data captured by the camera to determine whether there are abnormal conditions such as falling rocks damaging the photovoltaic panels or whether the photovoltaic panels are warping and deforming. If an abnormality is found, the warning reminder submodule is immediately triggered. When the abnormality judgment submodule detects that the photovoltaic panel is abnormal, the warning reminder submodule sends a warning signal to the data center. After receiving the warning signal, the data center immediately notifies the relevant staff to repair it. If it is determined that there is no abnormality in the photovoltaic panel, the train passes normally without affecting the driving efficiency.

[0083] In summary, this embodiment provides real-time, high-quality image data, provides an accurate information source for the abnormal judgment submodule, enhances the safety of train operation, and can promptly detect potential dangerous situations; improves the detection accuracy and speed of abnormal conditions of photovoltaic panels, reduces the possibility of missed reports and false alarms, and provides timely abnormal information to staff, helping them to quickly take repair measures to prevent accidents from expanding; establishes a rapid response mechanism to ensure timely handling of abnormal situations, improves the safety and reliability of train operation, reduces traffic accidents caused by abnormal photovoltaic panels, reduces operation and maintenance costs, and avoids more serious losses through timely repairs.

[0084] like Figure 2-Figure 4 As shown, this embodiment also provides an embodiment of a long-distance strip photovoltaic power generation control device for railways. In this embodiment, the long-distance strip photovoltaic power generation control device for railways is applied to the long-distance strip photovoltaic power generation control method for railways in the above-mentioned embodiment. The long-distance strip photovoltaic power generation control device for railways includes a track buckle assembly 1, a rail 2, a special-shaped support 3, a spray device with a memory storage function 4, a photovoltaic panel 5, a sleeper 6, an insulator 7, an anchor bolt 8, a buckle assembly 9, a cantilevered steel plate beam 10, a longitudinal connection clamp 11, a side anchor 12, a spring shock absorber 13, a longitudinal buckle 14, and a guide rail 15 for supporting a photovoltaic panel;

[0085] Among them, it is connected to the rail 2 through the track clip assembly 1 below the rail 2, an insulator 7 is arranged between the clip assembly 9 and the rail 2, and the clip assembly is connected and fixed by the anchor bolt 8; the cantilevered steel plate beam 10 is extended to form the supporting structure of the photovoltaic component, and is connected to the special-shaped support member 3 on the cantilevered steel plate beam 10 through the anchor bolt 8, and the upper side of the special-shaped support member 3 close to the rail 2 is connected to the upper photovoltaic panel 5 through the side anchor 12, and a spring shock absorber 13 is installed on the opposite side, and a longitudinal connecting clamp 11 is installed above the photovoltaic panel 5 at the installation position of the spring shock absorber 13; the photovoltaic panel 5 is located above the railway track, and a spray device 4 with a memory storage function is installed on the train above it and attached to the train, and the photovoltaic panel 5 is installed on the guide rail 15 supporting the photovoltaic panel, and the guide rail supporting the photovoltaic panel is fixed by the longitudinal clip 14.

[0086] Preferably, the photovoltaic panel of this embodiment is the core component, which is responsible for directly converting sunlight into electrical energy. It is installed above the railway track and connected to the rail through structural parts such as special-shaped supports 3 and cantilevered steel plate beams 10 to ensure stability and not hinder the operation of the train. The cantilevered steel plate beams 10 are picked out to form a supporting structure for the photovoltaic assembly, which is connected to the special-shaped supports 3 through anchor bolts 8. The upper side of the special-shaped supports 3 close to the rail 2 is connected to the photovoltaic panel 5 through side anchors 12 to ensure the stability and safety of the photovoltaic panel 5; an insulator 7 is provided between the snap assembly 9 and the rail 2 to prevent the current from interfering with or damaging the rail. The snap assembly 9 is connected and fixed by anchor bolts 8 to ensure the stability of the entire photovoltaic power generation system; the spray device 4 with memory storage function is attached to the vehicle, which is the core part of the intelligent spray device and can automatically start and spray water mist as needed.

[0087] In summary, the photovoltaic panel 5 of this embodiment directly converts sunlight into electrical energy and is the core component of the system. It uses the space between the railway tracks for photovoltaic power generation, which improves the utilization rate of land. The generated electricity can be used within the railway system or incorporated into the power grid, reducing dependence on traditional energy. The special-shaped support member 3 is turned up and connected to the photovoltaic panel 5 by the side anchor 12 on the side close to the rail 2 to ensure the stability and safety of the photovoltaic panel 5. The cantilevered steel plate beam 10 is selected to form a supporting structure for the photovoltaic assembly, which is connected to the special-shaped support member 3 by the anchor bolt 8 to provide a stable support for the photovoltaic panel 5. These structural members together constitute the support system of the photovoltaic panel 5, ensuring the stable operation of the photovoltaic panel 5 in a complex environment and improving the overall reliability and safety of the photovoltaic power generation system. An insulator 7 is arranged between the snap assembly 9 and the rail 2 to prevent the current from interfering with or damaging the rail 2. The snap assembly 9 is connected and fixed by an anchor bolt 8 to ensure the stability of the entire photovoltaic power generation system. The setting of the insulator 7 protects the normal operation of the rail 2 and avoids the current interference that may be caused by the photovoltaic power generation system. The fixing method of the anchor bolt 8 ensures the stability of the system and improves the service life of the system; the spray equipment 4 with memory storage function can automatically start and spray water mist as needed, has memory storage function, is attached to the train, and is the core part of the intelligent spray device. The memory storage function can record the operating status of the spray equipment, provide a basis for subsequent maintenance and optimization, reduce manual intervention, and improve the automation level of the railway system.

[0088] Furthermore, if Figure 2 and Figure 4 As shown, the support structure includes: a special-shaped support member 3, a photovoltaic panel 5, an anchor bolt 8, a longitudinal connection clamp 11, a side anchor 12, and a spring shock absorber 13;

[0089] Among them, the special-shaped support member 3 is connected to the cantilevered steel plate beam through the anchor bolt 8, and the upper side of the special-shaped support member 3 close to the rail is connected to the upper photovoltaic panel 5 through the side anchor 12, and a spring shock absorber 13 is installed on the opposite side, and a longitudinal connecting clamp 11 is installed above the photovoltaic panel 5 at the installation position of the spring shock absorber 13.

[0090] Preferably, the present embodiment is connected to the longitudinal special-shaped support member 3 on the cantilever steel plate beam 10 by bolts. The special-shaped support member 3 has a small horizontal stiffness, and therefore has a certain adaptive deformation ability in the lateral direction. When the photovoltaic module is affected by temperature and produces a constant linear displacement, it will not generate a lateral force on the rail 2; the vertical support member is a special-shaped structure, which has a large vertical support stiffness and a certain horizontal deformation ability. This can avoid deformation due to excessive temperature and generate lateral thrust on the rail, thereby avoiding affecting the smoothness of the rail; although the special-shaped support member 3 is special-shaped, it is easy to construct and is formed by cutting and extruding a piece of steel plate; the photovoltaic panel 5 is anchored in the lateral direction by two pressure blocks and in the longitudinal direction by side bolts at a certain interval, which fully guarantees the stability of the anchoring of the photovoltaic panel 5; the pressure buckle of the photovoltaic panel 5 adopts an elastic buckle strip to avoid damage to the photovoltaic panel 5 caused by hard contact.

[0091] In summary, the special-shaped support member 3 of this embodiment provides lateral adaptive deformation capability through a relatively small horizontal stiffness, ensuring that the photovoltaic module will not generate lateral force on the rail when the lateral linear displacement is generated by the temperature. The special-shaped structure provides a large vertical support stiffness and has a horizontal deformation capability, preventing the lateral thrust on the rail caused by deformation due to excessive temperature, maintaining the smoothness of the rail, ensuring the safety and stability of railway operation, and improving the adaptability and durability of the photovoltaic system; the photovoltaic panel 5 is anchored by a horizontal pressure block and a longitudinal side bolt to ensure the stability of the photovoltaic panel anchoring, and an elastic buckle strip is used as a pressure buckle to avoid damage to the photovoltaic panel caused by hard contact, thereby improving the installation firmness and service life of the photovoltaic panel and ensuring the efficient and stable operation of the photovoltaic system; the longitudinal connection clamp 11 is installed above the photovoltaic panel 5, further enhancing the connection stability and integrity between the photovoltaic panels 5, improving the wind pressure resistance and durability of the photovoltaic system, and ensuring the stable operation of the photovoltaic system under severe weather conditions;

[0092] like Figure 5 As shown, this embodiment also provides an embodiment of a railway long-distance strip photovoltaic power generation control method. In this embodiment, the railway long-distance strip photovoltaic power generation control method is applied to the railway long-distance strip photovoltaic power generation control system in the above embodiment. The railway long-distance strip photovoltaic power generation control method specifically includes the following steps:

[0093] Step S1: photovoltaic panels are continuously installed between rails to form a photovoltaic power generation system, and integrated into a strip photovoltaic power station to store electricity collected by the photovoltaic panels;

[0094] Step S2: Under the premise of ensuring the normal operation of the railway, the strip photovoltaic power station is decentralizedly connected to the railway power grid system through cables to supply electricity to the railway power grid;

[0095] Step S3: The spray facility is attached to the bottom of the train, and the camera is installed in front of the vehicle. The spray behavior and abnormal data are recorded through automatic sensing and data storage of the spray facility. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning or abnormal data feedback of the photovoltaic panels is realized through intelligent control.

[0096] Preferably, step S1 of this embodiment effectively utilizes the space resources along the railway by continuously installing photovoltaic panels between the rails, and integrates them into a strip photovoltaic power station, which can efficiently collect, convert and store solar energy to provide renewable energy for the railway system; step S2 realizes the seamless connection between photovoltaic power and the railway power grid, ensures the stable supply of electricity, and the decentralized access method reduces the impact on the power grid and improves the stability of the power system; step S3 realizes real-time monitoring and intelligent maintenance of photovoltaic panels, improves the power generation efficiency and service life of photovoltaic panels, and can accurately record spraying behavior and abnormal data through automatic sensing and data storage, providing strong support for subsequent maintenance and management.

[0097] To sum up, this embodiment promotes the use of green energy, reduces dependence on fossil fuels, is beneficial to environmental protection, provides a reliable source of electricity for the railway system, and enhances the self-sufficiency of the railway system; improves the energy utilization efficiency of the railway system, reduces operating costs, enhances the power supply reliability of the railway system, and provides a strong guarantee for the safe operation of the railway; reduces the maintenance cost of photovoltaic panels, improves the overall energy utilization efficiency, and realizes precise maintenance of photovoltaic panels through intelligent control, ensuring the stable operation of photovoltaic power stations, enhancing the intelligence level of the railway system, and promoting the green development of the railway industry.

[0098] Furthermore, if Figure 6 As shown, the control process of the spraying facility in step S3 specifically includes the following steps:

[0099] Step S31: The spraying facility is attached to the train, and the train is filled with clean water in the railway maintenance section;

[0100] Step S32: The spraying facility determines whether the photovoltaic panel needs to be cleaned according to the last spraying record provided by the data storage device or whether there is a mandatory cleaning instruction. If cleaning is required, the spraying facility is started; if cleaning is not required, the train leaves normally;

[0101] Step S33: During the process of the spraying facilities cleaning the photovoltaic panels, the spraying intensity is adjusted according to the spraying feedback. After the photovoltaic panels are cleaned, the train leaves.

[0102] Preferably, in step S31 of this embodiment, the spraying facilities are installed and filled with clean water, which provides the necessary hardware foundation and clean water source for intelligent spraying, and ensures that the spraying facilities can work normally; step S32 determines whether the photovoltaic panels need to be cleaned, and starts the spraying facilities, reduces unnecessary spraying through intelligent judgment, saves water resources and energy, and ensures that the photovoltaic panels are cleaned in time when needed; step S33 adjusts the spraying intensity according to the spraying feedback, and leaves after the cleaning is completed. The spraying intensity is adjusted through real-time feedback to ensure the cleaning effect while reducing waste. After the cleaning is completed, the train leaves in time without affecting the normal operation of the railway (refer to the attached schematic diagram for the specific principle diagram) Figure 7 ).

[0103] In summary, this embodiment improves the cleaning efficiency, realizes on-demand cleaning, and is beneficial to resource conservation and environmental protection; optimizes the cleaning process, improves resource utilization efficiency, and ensures smooth railway traffic; reduces unnecessary spraying through intelligent judgment, improves cleaning efficiency and resource conservation; optimizes the cleaning process, ensures cleaning effect and resource utilization efficiency, and does not affect the normal operation of the railway.

[0104] Furthermore, the process of starting the spraying facility in step S32 specifically includes the following steps:

[0105] Step S321: After the train enters the railway maintenance section and is filled with cleaning water, the spraying facility is first initialized; after passing the self-check, it enters the standby state; the spraying facility obtains the last spraying record through the data storage device, or receives a forced cleaning instruction; determines whether the photovoltaic panel needs to be cleaned; if the judgment result is that cleaning is required, proceed to the next step; if not, the train leaves normally;

[0106] Step S322: After determining that cleaning is required, the spraying facility starts preparation, including turning on the water pump, starting the motor of the spraying device, and adjusting the nozzle angle; at the same time, the initial spraying intensity is preset according to the current state of the photovoltaic panel (such as the degree of dust accumulation);

[0107] Step S323: The spraying facility starts to clean the photovoltaic panels. During the spraying process, the spraying effect is monitored in real time, and the spraying intensity is dynamically adjusted through the data fed back by the sensor. When the photovoltaic panels are cleaned, the spraying facility stops spraying, turns off the water pump and motor, and resets all components to the initial state.

[0108] Preferably, the initialization and data judgment of step S321 of this embodiment ensure that all key components are in normal working condition, avoiding spray failure or train delay caused by equipment failure; by obtaining the last spray record or forced cleaning instruction, it can intelligently judge whether the photovoltaic panel needs to be cleaned, avoid unnecessary spraying operations, and save water resources and energy. The significance achieved: through self-checking and data judgment, the spraying facilities are ensured to be in the best condition before starting, the failure rate is reduced, and the overall reliability of the system is improved; the cleaning needs of the photovoltaic panels are intelligently judged, unnecessary spraying operations are avoided, and water resources and energy are effectively saved, which is in line with the concept of sustainable development. Step S322 starts preparation to ensure that the spraying facilities can respond quickly and start working, reducing the startup delay; the initial spraying intensity is preset according to the current state of the photovoltaic panel to ensure the best spraying effect and avoid excessive or insufficient cleaning. The significance achieved: the spraying facilities are quickly started to ensure that the train stays in the maintenance section for the shortest time and improve the train operation efficiency; by presetting the initial spraying intensity, the photovoltaic panel cleaning effect is ensured to be the best, and the power generation efficiency and service life of the photovoltaic panel are improved. Step S323: Spray execution and reset. Through the data fed back by the sensor, the spray effect is monitored in real time and the spray intensity is adjusted dynamically to ensure the efficiency and accuracy of the cleaning process. After the cleaning is completed, the system automatically resets all components to the initial state to prepare for the next operation, ensuring the stability and repeatability of the system. Significance achieved: Through real-time monitoring and dynamic adjustment, the photovoltaic panel cleaning effect is guaranteed to be optimal, the cleaning efficiency is improved, and the cleaning time is reduced. After the cleaning is completed, it is automatically reset to ensure that the system can be restored to the best state after each operation, improving the stability and reliability of the system. Through efficient cleaning and reset operations, the spray facilities can be guaranteed to operate continuously and stably, providing guarantee for the long-term operation of the train.

[0109] In summary, the spraying facility in the present embodiment through the above steps can not only efficiently and accurately complete the cleaning task of the photovoltaic panels, but also achieve significant technical effects and practical significance in terms of resource utilization, system reliability and operating efficiency.

[0110] Furthermore, the process of determining whether the photovoltaic panel needs to be cleaned in step S321 specifically includes the following steps:

[0111] Step S3211: Collect a large amount of historical spray records from the database, including the time of each spray, the spray volume, the effect after spraying, etc.; identify the periodic law of photovoltaic panel cleaning through time series analysis;

[0112] Step S3212: Establish a relationship model between the cleaning cycle and the cleaning effect through regression analysis to predict the improvement of power generation efficiency after cleaning under different dust accumulation levels; and establish a cleaning demand model based on the prediction results;

[0113] Step S3213: Determine whether there is a forced cleaning instruction input. If there is a forced cleaning instruction input, automatically generate a cleaning decision based on the historical data and the content of the forced cleaning instruction, confirm the cleaning requirement level, and perform spraying; if there is no forced cleaning instruction, automatically generate a cleaning decision based on the historical data and perform spraying.

[0114] Preferably, the collection and analysis of historical spray records in step S3211 of this embodiment can accumulate rich data resources by collecting a large number of historical spray records, providing a basis for subsequent analysis; through time series analysis, the periodic laws of photovoltaic panel cleaning, such as seasonal changes, weather influences, etc., can be identified. Significance achieved: After identifying the periodic laws of cleaning, the cleaning cycle can be optimized, unnecessary cleaning can be avoided, and resource waste can be reduced; based on the time series analysis of historical data, the prediction accuracy of future cleaning needs can be improved to ensure that the photovoltaic panels are always in the best working state. Step S3212 regression analysis and cleaning demand model establishment, through regression analysis, establish a relationship model between the cleaning cycle and the cleaning effect, and quantify the improvement of power generation efficiency after cleaning under different dust accumulation levels; based on the results of regression analysis, establish a cleaning demand model, which can predict cleaning needs according to real-time data and generate corresponding cleaning decisions. Significance achieved: Through regression analysis, the cleaning effect can be quantified, providing a scientific basis for decision-making and avoiding blind cleaning; after establishing the cleaning demand model, the system can automatically generate cleaning decisions to improve decision-making efficiency and accuracy. Step S3213: Processing of forced cleaning instructions and automatic generation of cleaning decisions. It can identify and process forced cleaning instructions to ensure timely cleaning in special circumstances (such as severe dust accumulation); in the absence of forced cleaning instructions, the system can automatically generate cleaning decisions based on historical data to ensure the continuous and efficient operation of photovoltaic panels. Significance achieved: It can flexibly respond to forced cleaning instructions to ensure timely measures in special circumstances to avoid a decrease in power generation efficiency; by automatically generating cleaning decisions, the system can realize the automated management of photovoltaic panels, reduce manual intervention, and improve management efficiency.

[0115] In summary, this embodiment can scientifically and efficiently determine whether the photovoltaic panels need to be cleaned, ensure that the photovoltaic panels are always in the best working state, and maximize the power generation efficiency. It not only improves the economic benefits of the photovoltaic system, but also reduces resource waste, which is in line with the concept of sustainable development.

[0116] Furthermore, the process of establishing a cleaning demand model based on the prediction results in step S3212 specifically includes the following steps:

[0117] Step S32121: using a multi-level trend analysis method to identify the long-term trend, medium-term trend and short-term trend of the photovoltaic panel cleaning demand from historical data, and obtain the seasonal and cyclical laws of the cleaning demand;

[0118] Step S32122: polynomial regression is used for modeling, and a multi-stage training method is used to first perform coarse-grained training and then perform fine-grained adjustment to gradually optimize model parameters; nested cross-validation is used to evaluate the stability and accuracy of the model;

[0119] Step S32123: combining the confidence interval of the Bayesian evaluation prediction result, setting different thresholds of cleaning demand levels according to different cleaning needs; combining historical data, the prediction results of the regression model and the set thresholds, automatically generating the optimal cleaning decision;

[0120] The historical data, the prediction results of the regression model and the set threshold are integrated to form a comprehensive data set; the integrated data is analyzed through learning to identify the key factors of cleaning needs, such as cleaning frequency, cleaning effect, seasonal changes, etc.; decision rules are set based on the integrated data and analysis results; for example, when the predicted cleaning demand exceeds the set threshold, a cleaning decision is automatically generated;

[0121] Step S32124: Use natural language processing to parse the content of the forced cleaning instruction, merge and verify the forced cleaning instruction with historical data; if there is a forced cleaning instruction, give priority to executing the forced cleaning instruction; dynamically adjust the cleaning decision based on the content of the forced cleaning instruction and historical data.

[0122] Preferably, the multi-level trend analysis in step S32121 of this embodiment can comprehensively identify the long-term, medium-term and short-term trends of the cleaning demand of photovoltaic panels through the multi-level trend analysis method, help understand the dynamic changes of cleaning demand; identify the seasonal and periodic laws of cleaning demand, provide a more refined basis for prediction, and improve the accuracy of prediction. The significance achieved: Through multi-level trend analysis, the cleaning demand of photovoltaic panels can be more comprehensively understood, providing a solid foundation for subsequent modeling and decision-making; identifying seasonal and periodic laws helps to improve the accuracy of the prediction model and ensure accurate judgment of cleaning demand. Step S32122 polynomial regression modeling and multi-stage training, using polynomial regression for modeling, can capture the nonlinear relationship between variables and improve the explanatory power and predictive ability of the model; through the multi-stage training method, the model parameters are gradually optimized to improve the generalization ability and stability of the model; the nested cross-validation method is used to comprehensively evaluate the stability and accuracy of the model to ensure the reliability of the model. Significance achieved: Through polynomial regression and multi-stage training, the prediction accuracy of the model can be improved to ensure accurate judgment of cleaning needs; nested cross-validation ensures the stability and reliability of the model, reduces the risk of overfitting, and improves the generalization ability of the model. Step S32123 Bayesian evaluation and dynamic threshold setting, combined with the Bayesian method, evaluate the confidence interval of the prediction results, provide more reliable prediction information, and help decision makers better understand the prediction results; set different thresholds for cleaning demand levels according to different cleaning needs to ensure the rationality and timeliness of cleaning needs; combine historical data, the prediction results of the regression model and the set thresholds to automatically generate the optimal cleaning decision, and improve the scientificity and efficiency of the decision. Significance achieved: Through Bayesian evaluation, confidence intervals are provided to help decision makers better understand the prediction results and improve the reliability of decisions; dynamic threshold setting and intelligent decision generation can optimize the management of cleaning needs and ensure the rationality and timeliness of cleaning needs. Step S32124: forced cleaning instruction processing and dynamic decision adjustment. Natural language processing (NLP) technology is used to intelligently analyze the content of forced cleaning instructions to ensure accurate execution of instructions; the forced cleaning instructions are integrated and verified with historical data to ensure the rationality and feasibility of the instructions; in the case of forced cleaning instructions, the forced cleaning instructions are executed first to ensure the timeliness and effectiveness of cleaning; according to the content of the forced cleaning instructions and historical data, the cleaning decision is dynamically adjusted to ensure the optimization of the cleaning effect. The significance achieved: through natural language processing and analysis, the accurate execution of forced cleaning instructions is guaranteed, and the execution efficiency of instructions is improved; dynamic decision adjustment and priority processing can enhance the flexibility of decision-making and ensure the timeliness and effectiveness of cleaning needs; through data fusion and verification, the rationality and feasibility of cleaning decisions are guaranteed, the cleaning effect is optimized, and the power generation efficiency of photovoltaic panels is improved.

[0123] In summary, this embodiment can not only fully understand the cleaning needs of photovoltaic panels, but also improve the prediction accuracy and stability of the model, optimize the management and decision-making of cleaning needs, ensure the rationality and timeliness of cleaning needs, and ultimately improve the power generation efficiency of photovoltaic panels. It reflects the advancement and innovation of technology and provides a scientific and sophisticated solution for the cleaning needs management of photovoltaic panels.

[0124] Furthermore, if Figure 8 As shown, the process of the spraying facility in step S3 determining whether the photovoltaic panel is abnormal specifically includes the following steps:

[0125] Step S34: Install a camera in front of the train. After the warning device is activated, the camera starts to capture image data in front of the train.

[0126] Step S35: the early warning device determines whether there is rockfall damage to the photovoltaic panel, or whether the photovoltaic panel is warped and deformed, and determines whether there is an abnormality in the photovoltaic panel. If there is rockfall damage to the photovoltaic panel or the photovoltaic panel is warped and deformed, the photovoltaic panel is abnormal.

[0127] Step S36: If it is determined that the photovoltaic panel is abnormal, a warning signal is sent to the data center to remind relevant staff to take repair measures. If it is determined that there is no abnormality in the photovoltaic panel, the train passes normally.

[0128] Preferably, in step S34 of this embodiment, a camera is installed in front of the train, and image data in front of the train is captured after the early warning device is activated, so as to ensure real-time monitoring of the environment in front of the train during its movement; in step S35, the early warning device determines whether there is rockfall damage to the photovoltaic panel or whether the photovoltaic panel is warped and deformed by analyzing the image data captured by the camera, so as to determine whether there is an abnormality in the photovoltaic panel; in step S36, if it is determined that the photovoltaic panel is abnormal, the early warning device will send a warning signal to the data center to remind relevant staff to take repair measures; if it is determined that there is no abnormality, the train passes normally (for a specific schematic diagram, please refer to the attached Fig. 9 ).

[0129] To sum up, through real-time monitoring, this embodiment allows the train to promptly detect and respond to potential obstacles or abnormal situations, thereby improving driving safety; it achieves accurate judgment of the status of photovoltaic panels, which helps to promptly detect and resolve potential safety hazards and ensure the safety of facilities along the railway; it ensures timely discovery and rapid response to problems, avoids potential risks caused by abnormal photovoltaic panels, and also ensures the normal operation of the train. Through the warnings of the data center, relevant staff can quickly locate the problem and take corresponding measures, thereby improving work efficiency and safety.

[0130] Furthermore, the process of determining whether the photovoltaic panel is abnormal in step S35 specifically includes the following steps:

[0131] Step S351: A camera is installed in front of the train. After the warning device is activated, the camera starts to capture real-time image data in front of the train; the captured image data is pre-processed, including denoising, contrast enhancement and resolution adjustment;

[0132] Step S352: extracting rockfall features in the image, such as shape, color, and motion trajectory; comparing the features with the preset track range features, identifying the extracted features, and determining whether there is rockfall; after identifying the rockfall, locating the specific position of the rockfall in the image;

[0133] Step S353: extracting features of the photovoltaic panel, such as edge, texture and color distribution, from the real-time impact data, analyzing the features of the photovoltaic panel to determine whether there is warping deformation; after identifying the warping deformation, evaluating the degree of deformation to determine whether it reaches an abnormal threshold;

[0134] Step S354: Combine the results of rockfall detection and photovoltaic panel warping and deformation detection to comprehensively determine whether there is an abnormality in the photovoltaic panel; if it is determined that the photovoltaic panel is abnormal, a warning signal is generated and sent to the data center through wireless communication technology; after receiving the warning signal, the data center reminds relevant staff to take repair measures, and if there is no abnormality, the train passes normally;

[0135] Among them, the expression for comprehensively judging whether there is an abnormality in the photovoltaic panel is:

[0136]

[0137] Where: E: Overall Anomaly Index, used to determine whether there is an abnormality in the photovoltaic panel. The higher the E value, the greater the possibility of abnormality in the photovoltaic panel.

[0138] S i represents the score of the i-th rockfall detection, represents the result of the i-th rockfall detection, S i The higher the value, the more obvious the rockfall features detected; D i represents the i-th warping detection score (Warping Detection Score), which represents the result of the i-th photovoltaic panel warping detection. i The higher the value, the more obvious the warpage deformation detected; i represents the i-th time parameter (Time Parameter), which represents the time point of the i-th detection, T i The value is used to consider the impact of time factors on anomaly detection; C i The i-th environmental parameter (Environmental Parameter) indicates the impact of the i-th environmental factor on the state of the photovoltaic panel, such as light intensity, temperature, etc.; α i, β i , γ i , δ i represents the i-th weight coefficient, which is used to adjust the importance of each parameter in the comprehensive judgment; n represents the total number of test samples, m represents the total number of environmental parameters, ∈ j , j , η j ,θ j It represents the jth normalization coefficient, which is used to adjust the normalization effect of each parameter in the denominator; the denominator is a summation formula within the square root, which is used to normalize the comprehensive score of the numerator. The rockfall detection score S of each environmental parameter is j , Warpage detection score D j , time parameter T j and environmental parameters C j Square them respectively and multiply them by the corresponding normalization coefficient ε j , j , η j ,θ j Then the sum is calculated; if the E value exceeds the preset abnormal threshold, it is judged that there is an abnormality in the photovoltaic panel, and a warning signal is generated and sent through wireless communication technology; multiple parameters and characteristics are comprehensively considered, and through the combination of the numerator, denominator and summation formula, it is possible to more comprehensively and accurately judge whether there is an abnormality in the photovoltaic panel, thereby ensuring the safety of train operation and the reliability of the photovoltaic panel.

[0139] Preferably, in step S351 of this embodiment, the image data is captured and preprocessed to ensure that the captured image data has high clarity and details, providing high-quality input for subsequent analysis; by denoising, contrast enhancement and resolution adjustment, the clarity and contrast of the image data are improved, noise interference is reduced, and a more accurate data basis is provided for subsequent feature extraction and recognition. Significance: The preprocessing step ensures the quality of the image data, provides a reliable data basis for rockfall detection and photovoltaic panel warping deformation detection, and improves the accuracy and reliability of the overall detection; real-time capture and preprocessing of image data ensures the real-time nature of the detection process, and can detect abnormal situations in the first place. Step S352 rockfall detection extracts rockfall features in the image, such as shape, color and motion trajectory, to provide key information for rockfall identification; by comparing with the preset track range features, image recognition technology is used to determine whether there is rockfall, thereby improving the accuracy of rockfall detection; after identifying the rockfall, the specific position of the rockfall in the image is further located to determine whether it poses a threat to the photovoltaic panel, thereby improving the refinement of the detection. Significance: Through rockfall detection, the potential threat of rockfall to photovoltaic panels can be discovered and warned in time, ensuring the safe operation of photovoltaic panels; through rockfall positioning, preventive maintenance measures can be taken in advance to avoid equipment damage and safety hazards caused by rockfall. Step S353 Photovoltaic panel warping deformation detection, extracting the characteristics of photovoltaic panels from real-time image data, such as edges, textures and color distribution, to provide key information for warping deformation identification; through image recognition technology, analyzing the characteristics of photovoltaic panels to determine whether warping deformation exists, thereby improving the accuracy of deformation detection; after identifying warping deformation, further evaluating the degree of deformation to determine whether it reaches the abnormal threshold, thereby improving the refinement of detection. Significance: Through warping deformation detection, the status of photovoltaic panels can be monitored in real time, potential equipment abnormalities can be discovered and warned in time, ensuring the normal operation of photovoltaic panels; through deformation degree assessment, a scientific basis can be provided for maintenance decisions to avoid production interruptions and safety hazards caused by equipment abnormalities. Step S354 abnormality judgment and decision-making, combined with the results of rockfall detection and photovoltaic panel warping and deformation detection, comprehensively judge whether there is an abnormality in the photovoltaic panel, which improves the comprehensiveness and accuracy of the judgment; if it is judged that the photovoltaic panel is abnormal, a warning signal is generated and sent to the data center through wireless communication technology, which improves the timeliness and reliability of the warning; after receiving the warning signal, the data center reminds the relevant staff to take repair measures, and if there is no abnormality, the train passes normally, which improves the scientificity and rationality of the decision. Significance: Through comprehensive judgment and warning signal generation, it can timely warn and handle the abnormal situation of the photovoltaic panel to ensure the safe operation of the photovoltaic panel; through wireless communication technology and decision-making execution of the data center, the automatic management of abnormal detection and processing of photovoltaic panels is realized, and the management efficiency and response speed are improved.

[0140] In summary, the photovoltaic panel abnormality detection process of this embodiment achieves high-precision, real-time and automated detection and early warning, ensures the safe operation of the photovoltaic panels and the normal maintenance of the equipment, and has important technical effects and practical significance.

[0141] Furthermore, the process of determining whether warping deformation exists in step S353 specifically includes the following steps:

[0142] Step S3531: extracting the features of the photovoltaic panel from the pre-processed image data; extracting by edge detection algorithm, texture features can be obtained by texture analysis, and color distribution by color histogram analysis;

[0143] Step S3532: Analyze whether the shape of the photovoltaic panel is deformed by Hough transform; judge whether the photovoltaic panel is warped by the change of texture features, and the change of texture uniformity or symmetry may indicate that the photovoltaic panel is warped; judge whether the photovoltaic panel is warped by the change of color distribution, and the non-uniformity of color distribution may indicate that the surface of the photovoltaic panel is deformed;

[0144] Step S3533: Calculate the degree of change in the curvature or texture of the edge of the photovoltaic panel to quantify the size of the deformation; compare the quantified deformation degree with the preset abnormal threshold to determine whether the deformation reaches the abnormal threshold; combine the results of rockfall detection and photovoltaic panel warping deformation detection to comprehensively determine whether there is an abnormality in the photovoltaic panel; if it is determined that the photovoltaic panel is abnormal, generate a warning signal.

[0145] Preferably, the feature extraction of step S3531 of this embodiment can accurately identify the edge of the photovoltaic panel and provide basic data for subsequent shape analysis; by analyzing the texture features, it is possible to detect slight changes on the surface of the photovoltaic panel, which may indicate warping or deformation; by analyzing the color distribution, it is possible to detect the color non-uniformity on the surface of the photovoltaic panel, which may indicate that the surface has been deformed. Significance achieved: It provides key data for shape and deformation analysis to ensure the accuracy and reliability of the analysis; through multi-dimensional feature extraction, it is possible to more comprehensively capture the state changes of the photovoltaic panel and improve the sensitivity and accuracy of the detection. Step S3532 shape analysis can identify the shape changes of the photovoltaic panel, especially the changes of straight lines and curves, so as to determine whether there is warping; by analyzing the uniformity and symmetry of the texture, it is possible to determine whether the photovoltaic panel has warped; by analyzing the non-uniformity of the color distribution, it is possible to further confirm the deformation of the photovoltaic panel surface. Significance achieved: Through the analysis of shape and texture, it is possible to intuitively determine whether the photovoltaic panel has warped and deformed, providing a basis for subsequent quantitative analysis; combined with the changes in color distribution, it is possible to more comprehensively evaluate the state of the photovoltaic panel and improve the accuracy of the judgment. Step S3533: Quantitative analysis and comprehensive judgment: By calculating the curvature of the edge of the photovoltaic panel, the deformation can be quantified to provide data support for the subsequent threshold comparison; by quantifying the degree of texture change, the deformation of the photovoltaic panel can be further confirmed; the quantified deformation degree is compared with the preset abnormal threshold to determine whether the deformation has reached an abnormal level; combined with the results of rockfall detection and photovoltaic panel warping deformation detection, a comprehensive judgment is made to ensure the comprehensiveness and accuracy of the judgment. Significance achieved: Through quantitative analysis, the deformation degree of the photovoltaic panel can be accurately evaluated to provide a scientific basis for subsequent maintenance and repair; comprehensive judgment can ensure the comprehensiveness and reliability of the test results and avoid misjudgment of a single indicator; generate warning signals to promptly remind relevant personnel to handle the problem and ensure the safety and stable operation of the photovoltaic system.

[0146] In summary, this embodiment can not only accurately determine whether the photovoltaic panel is warped, but also quantify the size of the deformation and make a comprehensive judgment in combination with other test results to ensure the safety and stable operation of the photovoltaic system. The significance lies in improving the maintenance efficiency of the photovoltaic system, reducing the losses caused by the deformation of the photovoltaic panel, and ensuring the long-term stable operation of the photovoltaic system.

[0147] like Fig.10 As shown, this embodiment provides an embodiment of an electronic device. In this embodiment, the electronic device 16 includes a processor 161 and a memory 162 coupled to the processor 161 .

[0148] The memory 162 stores program instructions for implementing the railway long-distance strip photovoltaic power generation control method according to any of the above embodiments.

[0149] The processor 161 is used to execute the program instructions stored in the memory 162 to carry out the layout of the railway long-distance strip photovoltaic power generation control device.

[0150] The processor 161 may also be referred to as a CPU (Central Processing Unit). The processor 161 may be an integrated circuit chip having signal processing capabilities. The processor 161 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0151] Further, Fig.11 The schematic diagram of the structure of the storage medium of an embodiment of the present application is that the storage medium 17 of the embodiment of the present application stores program instructions 171 that can implement all the above methods, wherein the program instructions 171 can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0152] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0153] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units. The above is only an implementation mode of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present invention.

[0154] The specific implementation methods of the invention are described in detail above, but they are only examples, and the invention is not limited to the specific implementation methods described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the invention, therefore, the equalization, modification, improvement, etc. made without departing from the spirit and principle of the invention should be included in the scope of the invention.

Claims

1. A railway long-distance strip photovoltaic power generation control system, characterized in that: The railway long-distance strip photovoltaic power generation control system comprises: Photovoltaic power generation module, used to continuously install photovoltaic panels between rails to form a photovoltaic power generation system, and integrated into a strip photovoltaic power station to store the electricity collected by the photovoltaic panels; The power grid access module is used to connect the strip photovoltaic power station to the railway power grid system in a decentralized manner through cables to supply electricity to the railway power grid under the premise of ensuring the normal operation of the railway; The cleaning warning module is used to attach the spraying facilities to the bottom of the train, and the camera is installed in front of the vehicle. The spraying behavior and abnormal data are recorded through automatic sensing and data storage of the spraying facilities. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning or abnormal data of the photovoltaic panels are fed back through intelligent control.

2. A railway long-distance strip photovoltaic power generation control device, which is applied to the railway long-distance strip photovoltaic power generation control system as claimed in claim 1, characterized in that: The railway long-distance strip photovoltaic power generation control device includes: a track buckle assembly, a rail, a special-shaped support, a spray device with a memory storage function, a photovoltaic panel, a sleeper, an insulator, an anchor bolt, a buckle assembly, a cantilever steel plate beam, a longitudinal connection clamp, a side anchor, a spring shock absorber, a longitudinal buckle, and a guide rail supporting the photovoltaic panel; Among them, the rail is connected to the rail through the track clip assembly under the rail, an insulator is arranged between the clip assembly and the rail, and the clip assembly is connected and fixed by anchor bolts; the cantilevered steel plate beam is extended to form the supporting structure of the photovoltaic module, and is connected to the special-shaped support member on the cantilevered steel plate beam through anchor bolts, and the special-shaped support member is connected to the upper photovoltaic panel through the side anchor member on the side close to the rail, and a spring shock absorber is installed on the opposite side, and a longitudinal connection clamp is installed above the photovoltaic panel where the spring shock absorber is installed; the photovoltaic panel is located above the railway track, and a spray device with a memory storage function is installed on the train above it, and is attached to the train, and the photovoltaic is installed on the guide rail supporting the photovoltaic panel, and the guide rail supporting the photovoltaic panel is fixed by a longitudinal clip; The special-shaped support is connected to the cantilevered steel plate beam through anchor bolts, and the upper side of the special-shaped support close to the rail is connected to the upper photovoltaic panel through side anchors. A spring shock absorber is installed on the opposite side, and a longitudinal connecting clamp is installed above the photovoltaic panel at the installation position of the spring shock absorber.

3. A railway long-distance strip photovoltaic power generation control method, which is applied to the railway long-distance strip photovoltaic power generation control system as claimed in claim 1, characterized in that: The railway long-distance strip photovoltaic power generation control method comprises: Photovoltaic panels are installed continuously between the rails to form a photovoltaic power generation system, which is integrated into a strip photovoltaic power station to store the electricity collected by the photovoltaic panels; Under the premise of ensuring the normal operation of the railway, the strip photovoltaic power station is decentralizedly connected to the railway power grid system through cables to supply electricity to the railway power grid; The spraying facilities are attached to the bottom of the train, and the camera is installed in front of the vehicle. The spraying behavior and abnormal data are recorded through automatic sensing and data storage of the spraying facilities. When the train passes, it is judged in advance whether the photovoltaic panels need to be cleaned or abnormalities occur, and the spray cleaning of the photovoltaic panels or the feedback of abnormal data is realized through intelligent control.

4. The railway long-distance strip photovoltaic power generation control method according to claim 3 is characterized in that: The control process of the spraying facilities includes: The spraying facilities are attached to the trains and the trains are filled with clean water in the railway maintenance section; The spraying facility determines whether the photovoltaic panels need to be cleaned according to the last spraying record provided by the data storage device or whether there is a mandatory cleaning instruction. If cleaning is required, the spraying facility is started; if cleaning is not required, the train leaves normally; During the process of cleaning the photovoltaic panels with the spraying facilities, the spraying intensity is adjusted according to the spraying feedback. After the photovoltaic panels are cleaned, the train leaves.

5. The railway long-distance strip photovoltaic power generation control method according to claim 4 is characterized in that: The process of starting the sprinkler facility includes: After the train enters the railway maintenance section and is filled with cleaning water, the spray facility is first initialized; after passing the self-inspection, it enters the standby state; the spray facility obtains the last spray record through the data storage device, or receives a forced cleaning instruction; determines whether the photovoltaic panel needs to be cleaned; if the judgment result is that cleaning is required, it proceeds to the next step; if not, the train leaves normally; After determining that cleaning is needed, the spraying facility begins preparation, including turning on the water pump, starting the motor of the spraying device, and adjusting the nozzle angle; at the same time, the initial spraying intensity is preset according to the current state of the photovoltaic panel; The spraying facility starts to clean the photovoltaic panels. During the spraying process, the spraying effect is monitored in real time, and the spraying intensity is dynamically adjusted through data fed back by the sensors. When the photovoltaic panels are cleaned, the spraying facility stops spraying, turns off the water pump and motor, and resets all components to their initial state.

6. The railway long-distance strip photovoltaic power generation control method according to claim 5, characterized in that: The process of determining whether a photovoltaic panel needs cleaning includes: Collect a large amount of historical spray records from the database, including the time, amount and effect of each spray; identify the periodicity of photovoltaic panel cleaning through time series analysis; Through regression analysis, a relationship model between cleaning cycle and cleaning effect is established to predict the improvement of power generation efficiency after cleaning under different dust accumulation levels; a cleaning demand model is established based on the prediction results; Determine whether there is a forced cleaning instruction input. If there is a forced cleaning instruction input, the historical data and the content of the forced cleaning instruction are automatically used to generate a cleaning decision, confirm the cleaning requirement level, and perform spraying; if there is no forced cleaning instruction, the cleaning decision is automatically generated according to the historical data and spraying is performed.

7. The railway long-distance strip photovoltaic power generation control method according to claim 6, characterized in that: The process of building a cleaning demand model based on the forecast results includes: A multi-level trend analysis method is used to identify the long-term, medium-term and short-term trends of photovoltaic panel cleaning demand from historical data, and the seasonal and cyclical patterns of cleaning demand are obtained; Polynomial regression is used for modeling. Through a multi-stage training method, coarse-grained training is first performed, followed by fine-grained adjustment, to gradually optimize model parameters. Nested cross-validation is used to evaluate the stability and accuracy of the model. Combined with the confidence interval of the Bayesian evaluation prediction results, different thresholds for cleaning demand levels are set according to different cleaning needs; combined with historical data, the prediction results of the regression model and the set thresholds, the optimal cleaning decision is automatically generated; The historical data, the prediction results of the regression model and the set threshold are integrated to form a comprehensive data set; the integrated data is analyzed through learning to identify the key factors of cleaning needs, such as cleaning frequency, cleaning effect, and seasonal changes; decision rules are set based on the integrated data and analysis results; when the predicted cleaning demand exceeds the set threshold, a cleaning decision is automatically generated; Natural language processing is used to parse the content of the forced cleaning instructions, and the forced cleaning instructions are integrated and verified with historical data. In the case of forced cleaning instructions, the forced cleaning instructions are executed first; and the cleaning decisions are dynamically adjusted according to the content of the forced cleaning instructions and historical data.

8. The railway long-distance strip photovoltaic power generation control method according to claim 3 is characterized in that: The process of spraying facilities to determine whether the photovoltaic panels are abnormal includes: The camera is installed in front of the train. After the warning device is activated, the camera starts to capture image data in front of the train. The early warning device determines whether there is rockfall damage to the photovoltaic panel, or whether the photovoltaic panel is warped and deformed. If there is rockfall damage to the photovoltaic panel or the photovoltaic panel is warped and deformed, the photovoltaic panel is abnormal; If the photovoltaic panel is judged to be abnormal, a warning signal will be sent to the data center to remind relevant staff to take repair measures. If the photovoltaic panel is judged to be normal, the train will pass normally.

9. The railway long-distance strip photovoltaic power generation control method according to claim 8, characterized in that: The process of judging whether there is an abnormality in the photovoltaic panel includes: A camera is installed in front of the train. After the warning device is activated, the camera starts to capture real-time image data in front of the train. The captured image data is pre-processed, including denoising, contrast enhancement and resolution adjustment. Extract the features, shape, color and movement trajectory of the rockfall in the image; compare with the preset track range features, identify the extracted features, and determine whether there is a rockfall; after identifying the rockfall, locate the specific position of the rockfall in the image; Extract the features, edges, textures and color distribution of photovoltaic panels from real-time impact data, analyze the features of photovoltaic panels and determine whether there is warping deformation; after identifying the warping deformation, evaluate the degree of deformation and determine whether it reaches the abnormal threshold; Combining the results of rockfall detection and photovoltaic panel warping and deformation detection, a comprehensive judgment is made whether there is any abnormality with the photovoltaic panel. If it is judged that the photovoltaic panel is abnormal, a warning signal is generated and sent to the data center through wireless communication technology. After receiving the warning signal, the data center reminds relevant staff to take repair measures. If there is no abnormality, the train passes normally.

10. The railway long-distance strip photovoltaic power generation control method according to claim 9, characterized in that: The process of determining whether warping occurs includes: From the preprocessed image data, the features of the photovoltaic panels are extracted through edge detection algorithm, the texture features are obtained through texture analysis, and the color distribution is analyzed through color histogram; Hough transform is used to analyze whether the shape of the photovoltaic panel is deformed; the change in texture features is used to determine whether the photovoltaic panel is warped. Changes in texture uniformity or symmetry may indicate that the photovoltaic panel is warped; changes in color distribution are used to determine whether the photovoltaic panel is warped. Inhomogeneity in color distribution may indicate that the surface of the photovoltaic panel is deformed. Calculate the degree of change in the curvature or texture of the edge of the photovoltaic panel to quantify the size of the deformation; compare the quantified deformation degree with the preset abnormal threshold to determine whether the deformation reaches the abnormal threshold; combine the results of rockfall detection and photovoltaic panel warping deformation detection to comprehensively determine whether there is an abnormality in the photovoltaic panel; if the photovoltaic panel is judged to be abnormal, generate a warning signal.

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