Cleaning demand generation method and system based on power generation parameters

Abstract

The invention provides a cleaning demand generation method and system based on power generation parameters, belongs to the technical field of intelligent cleaning systems, and solves the problems that existing cleaning operation and maintenance are not refined enough, and intelligent management is lacked. The system comprises a cleaning system holder, a meteorological detector, a visual inspection mechanism, a dust thickness monitoring mechanism, a cleaning mechanism, a walking frame mechanism and an electric cabinet, a storage battery and a main control computer are arranged in the electric cabinet, and a data processing subsystem, a data modeling subsystem, a cleaning plan making subsystem and a cleaning feedback subsystem are arranged on the main control computer; the method comprises the following generation steps: early-stage preparation; data acquisition and transmission; processing and analyzing data; carrying out data modeling; cleaning requirement judgment; making a cleaning plan; cleaning operation is executed and fed back; and cleaning technology and equipment upgrading. The robot walks stably, is clean and efficient, can adjust operation parameters and cleaning strategies in real time, efficiently utilizes light energy, and enables a photovoltaic module to exert the maximum power generation efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent cleaning systems, and relates to a method for generating cleaning requirements based on power generation parameters, and in particular to a system for generating cleaning requirements based on power generation parameters. Background Art

[0002] Photovoltaic power generation is a technology that uses the photovoltaic effect of semiconductor interfaces to directly convert light energy into electrical energy. It is mainly composed of three parts: solar panels, controllers and inverters, and the main components are composed of electronic components. After solar cells are connected in series and packaged for protection, they can form a large-area solar cell module, which is then combined with power controllers and other components to form a photovoltaic power generation device.

[0003] With the development and application of renewable energy, photovoltaic power stations have become an important part of the clean energy field. However, photovoltaic power stations face a series of challenges in long-term operation. Photovoltaic panels are exposed to the outdoor environment for a long time and are easily affected by factors such as dust and rain, which leads to surface contamination and light loss, thereby reducing power generation efficiency. Traditional manual inspection and cleaning methods are inefficient, costly, and have safety hazards. There is a lack of intelligent management, the efficiency cannot be integrated for real-time evaluation, and there is a lack of intelligent cleaning systems.

[0004] After searching, as disclosed in Chinese patent document 202110600983.2, a photovoltaic panel cleaning method. This photovoltaic panel cleaning and dust removal device includes a portal support frame, a cleaning rod, a spray assembly and a control assembly. A first cavity is provided in the portal support frame, a first telescopic mechanism is provided in the first cavity, a first rotating mechanism is provided on the top of the first telescopic mechanism, the cleaning rod is connected to the first rotating mechanism through a second rotating mechanism, a cleaning cloth is attached to one side of the surface of the cleaning plate, and a brush head is provided on the other side of the surface of the cleaning rod. The control assembly is respectively connected to the first telescopic mechanism, the first rotating mechanism, the second rotating mechanism and the spray assembly to control the extension and contraction of the first telescopic mechanism, control the rotation of the first rotating mechanism or the second rotating mechanism, and control the spray assembly to spray cleaning liquid or natural water; although the present invention can use different methods to clean the photovoltaic panel according to the inclination angle of the photovoltaic panel, it is highly practical. However, it is impossible to effectively generate an automatic cleaning solution through intelligent data collection and analysis to improve the efficiency of photovoltaic power generation.

[0005] Based on this, we propose a cleaning demand generation method and system based on power generation parameters, which is stable, clean and efficient. It can adjust the operating parameters and cleaning strategies in real time, efficiently utilize light energy, and maximize the power generation efficiency of photovoltaic modules. Summary of the invention

[0006] The purpose of the present invention is to address the above-mentioned problems in the existing technology and propose a method and system for generating cleaning requirements based on power generation parameters. The technical problem to be solved by the invention is: how to make the system run stably, cleanly and efficiently, adjust the operating parameters and cleaning strategies in real time, efficiently utilize light energy, and maximize the power generation efficiency of photovoltaic modules.

[0007] The purpose of the present invention can be achieved by the following technical solutions: A cleaning demand generation system based on power generation parameters comprises a cleaning system pan / tilt, a meteorological detector, a visual inspection mechanism, a dust thickness monitoring mechanism, a cleaning mechanism, a walking frame mechanism and an electric control box, wherein the meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the electric control box are all arranged on the walking frame mechanism, a battery and a main control machine are arranged inside the electric control box, the main control machine is respectively electrically connected to the cleaning system pan / tilt, the battery, the meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the walking frame mechanism, a data processing subsystem, a data modeling subsystem, a cleaning plan formulation subsystem and a cleaning feedback subsystem are arranged on the main control machine, and the cleaning system pan / tilt is respectively electrically connected to a terminal device, a third-party weather data interface, an API data interface of a charging station and an inverter data collection interface.

[0008] The working principle of the present invention is as follows: the walking frame mechanism drives the meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the electric control box to move, the visual inspection mechanism accurately monitors the solar photovoltaic panels and the ground where the solar photovoltaic panels are located, controls the walking frame mechanism to walk on both sides of the solar photovoltaic panels, and the cleaning mechanism cleans the solar photovoltaic panels. During the cleaning process, the dust thickness monitoring mechanism monitors the dust thickness of the solar photovoltaic panels before and after cleaning to obtain the degree of cleanliness. The meteorological detector is used for real-time meteorology of the solar photovoltaic station, and the terminal device can receive information in real time and remotely control related equipment. The third-party weather data interface integrates the weather forecast data source to obtain weather forecast information for the next few days. The API data interface of the charging station and the inverter data acquisition interface obtain the power generation power, voltage and other data of the power station in real time. The data processing subsystem preprocesses the data collected in the database. The data modeling subsystem performs power generation modeling based on the processed data and analysis results. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the results of the cleaning demand judgment. The cleaning feedback subsystem optimizes and adjusts the cleaning demand judgment model and the cleaning plan based on the feedback of the cleaning effect.

[0009] The triangular frame walking adjustment subsystem includes a triangular frame, and hinged seats are fixed at the four corners of the lower end of the triangular frame, and telescopic electric push rods are fixed at the lower ends of the hinged seats. A rotating plate is fixed at the lower ends of the telescopic electric push rods, and a motor rotation seat is rotatably provided at the lower end of the rotating plate. The motor output shaft of the motor rotation seat is fixedly connected to the rotating plate, and a shock-absorbing spring rod and four telescopic sleeve rods are provided at the lower end of the motor rotation seat. A double-axis motor seat is provided at the lower ends of a shock-absorbing spring rod and four telescopic sleeve rods, and moving wheels are fixed on the motor output shafts at both ends of the double-axis motor seat, and a connecting seat is fixed between the two telescopic electric push rods on the same side. The meteorological detector is fixed at the middle of the upper end of the triangular frame, and the electric control box is arranged on the triangular frame.

[0010] With the above structure, the two telescopic electric push rods on both sides cooperate with the connecting seat, and the articulated seat cooperates with the telescopic electric push rod to adjust the height and inclination of the triangular frame to match the inclination angle of the photovoltaic panel. Each telescopic electric push rod can be raised and lowered individually to ensure that the device matches the concave and convex shape of the ground when moving, ensuring that the height and inclination of the triangular frame remain unchanged. The motor output shafts at both ends of the dual-axis motor seat drive the moving wheels to rotate for walking. A shock-absorbing spring rod and four telescopic sleeve rods cooperate to stabilize the motor rotation seat and the dual-axis motor seat to avoid strong shaking. The motor output shaft of the motor rotation seat drives the rotating plate to rotate, thereby driving the dual-axis motor seat to rotate. The four motor rotation seats cooperate to enable the device to turn and move.

[0011] The visual inspection mechanism includes a plurality of visual sensors and a plurality of visual cameras. The plurality of visual sensors are fixed on the dual-axis motor seats at corresponding positions, and the visual cameras are fixed on the four upper corners of the triangular frame.

[0012] With the above structure, several visual sensors and several visual cameras are used together for inspection to collect fault information of the photovoltaic power station and data such as the concave and convex shape of the ground of the photovoltaic station, which is convenient for mobile inspection.

[0013] The cleaning mechanism includes a water spray assembly, a hot air assembly, a dust collection box and a positioning assembly. The water spray assembly, the hot air assembly and the dust collection box are arranged at the upper end of the triangular frame, the positioning assembly is arranged in the middle of the lower end of the triangular frame, a water absorption roller is arranged at the lower end of the positioning assembly, a dust brushing spray assembly is arranged on the front side of the water absorption roller, and a hot air exhaust box is arranged on the rear side of the water absorption roller.

[0014] With the above structure, the positioning component adjusts the angles of the dust brushing spray component, the water absorption roller and the hot air exhaust box to match the inclined photovoltaic panel. The dust brushing spray component brushes the photovoltaic panel, and the dust brushed up is adsorbed inside the dust collecting box by the hot air component and the dust collecting box for regular and quantitative treatment. The water spray component is filled with water and cooperates with the dust brushing spray component to spray and clean the photovoltaic panel after dust brushing. The water absorption roller absorbs water and wipes the cleaned photovoltaic panel dry. The hot air component cooperates with the hot air exhaust box to dry the photovoltaic panel after wiping.

[0015] The water spray assembly includes a water tank and a water pump, both of which are fixed on the upper end of the triangular frame, and the water inlet end of the water pump is connected to the water tank through a pipeline; the hot air assembly includes a hot air box and a fan, both of which are fixed on the upper end of the triangular frame, the air outlet end of the fan is connected to the air inlet end of the hot air box through a pipeline, and the air inlet end of the fan is connected to the air outlet end of the dust collecting box through a pipeline; the positioning assembly includes a mounting base plate, which is fixed to the middle part of the lower end of the triangular frame, and the lower end of the mounting base plate is hinged with a swing electric push rod and an articulated connecting rod, the end of the swing electric push rod is hinged on the articulated connecting rod, and a rotating motor seat is fixed to the lower end of the articulated connecting rod, and a mounting frame is fixed to the motor output shaft of the rotating motor seat; the water suction roller component includes a water suction roller cover, The water suction roller cover is fixed at the lower end of the mounting frame, and a water suction roller is rotatably arranged inside the water suction roller cover; the dust brushing and spraying assembly comprises a dust removal cover, which is fixed at the front side of the water suction roller cover, and a dust suction duct is arranged on the front side of the dust removal cover, and the dust suction duct is connected to the air inlet end of the dust collecting box through a pipe, and a dust brush roller is rotatably arranged in the middle position inside the dust removal cover, and a spray pipe is arranged on the rear side of the dust removal cover, and a water injection pipe is connected to the spray pipe, and the water injection pipe extends out of the dust removal cover, and the water injection pipe is connected to the water outlet end of the water pump through a pipe; a power motor is fixed to the side of the dust removal cover, and the output shaft of the power motor is transmission-connected to the rotating shaft of the dust brush roller and the rotating shaft of the water suction roller; an air duct connected to the upper end of the hot air exhaust box is provided, and the air duct is connected to the air outlet end of the hot air box through a pipe.

[0016] With the above structure, the electric push rod is extended and retracted to drive the hinged connecting rod to be raised or swung down, and the hinged connecting rod drives the rotating motor seat to be raised or swung down, so as to adjust the angles of the dust brushing spray assembly, the water absorption roller and the hot air exhaust box to match the inclined photovoltaic panel; the output shaft of the power motor drives the dust brushing roller to rotate, and the dust brushing roller brushes the dust on the photovoltaic panel to the dust suction pipe. The dust suction pipe is connected to the air inlet end of the dust collecting box through a pipe, and the fan sucks air to form a negative pressure inside the dust collecting box, so that the brushed dust is sucked into the dust collecting box for regular and quantitative treatment; the water pump injects the clean water inside the water tank into the spray pipe through the pipe and the water injection pipe to spray and clean the photovoltaic panel after dust brushing; the output shaft of the power motor drives the water absorption roller to rotate, and absorbs water and wipes the cleaned photovoltaic panel; the fan blows cold air into the hot air box to form hot air, and the hot air is injected into the hot air exhaust box through the air guide pipe and blows on the photovoltaic panel to dry the photovoltaic panel after water wiping.

[0017] The dust thickness monitoring mechanism comprises a plurality of infrared sensors and a plurality of laser sensors, and the plurality of infrared sensors and the plurality of laser sensors are respectively and alternately fixed on the front side of the dust removal cover and the rear side of the hot air exhaust box.

[0018] With the above structure, several infrared sensors and several laser sensors cooperate to monitor the solar photovoltaic panels before and after cleaning to obtain dust thickness data.

[0019] The data processing subsystem preprocesses the collected data, and the preprocessing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, deeply mine and analyze the power generation parameters, and find out the characteristic information related to the cleaning demand. The data modeling subsystem performs power generation modeling based on the processed data and analysis results. The model includes but is not limited to a theoretical power generation prediction model, a theoretical power generation real-time monitoring model and a cleaning cycle optimization model. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the model and the suggestions of the decision support system. The cleaning plan should include but is not limited to the time, method, intensity, execution frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. The cleaning feedback subsystem performs the cleaning operation according to the cleaning plan. After the cleaning operation is completed, the power generation parameters of the photovoltaic module are monitored again to evaluate the cleaning effect; based on the feedback on the cleaning effect, the cleaning demand judgment model and the cleaning plan are optimized and adjusted.

[0020] A method for generating clean demand based on power generation parameters, comprising the following generating steps: Step 1: Preliminary preparation: Install generation equipment in the PV power station, establish a database to store the real-time monitored power generation parameter data and weather condition data, collect PV module brand data and laboratory theoretical data, and determine the rated efficiency of PV modules; Step 2, data collection and transmission: collect various data in real time, including but not limited to dust thickness, PV power station environmental meteorological data, future weather forecast data, PV power station inverter reading data and PV power station unattended inspection data, and transmit the collected data to the database in real time; Step 3: Data processing and analysis: pre-process the data collected in the database. The pre-processing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, conduct in-depth mining and analysis of power generation parameters, analyze the correlation between power generation parameters and cleaning requirements, and find out the characteristic information that affects cleaning requirements; Step 4: Data modeling: Based on the processed data and analysis results, power generation modeling is performed, and the model includes but is not limited to a theoretical power generation prediction model, a theoretical power generation real-time monitoring model, and a cleaning cycle optimization model; Step 5: Cleaning demand judgment: Use the established cleaning demand judgment model to judge the power generation parameter data monitored in real time, and determine whether cleaning is needed and the priority of cleaning based on the judgment results; Step 6: Formulate a cleaning plan: Develop a cleaning optimization plan based on the results of the cleaning needs assessment. The cleaning plan should include but not be limited to the time, method, intensity, frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. Step 7: Cleaning operation execution and feedback: Execute the cleaning operation according to the cleaning plan. After the cleaning operation is completed, monitor the power generation parameters of the PV modules again to evaluate the cleaning effect. According to the feedback of the cleaning effect, optimize and adjust the cleaning demand judgment model and the cleaning plan. Step 8: Cleaning technology and equipment upgrade: Pay attention to the latest developments in photovoltaic cleaning technology, introduce and apply advanced cleaning technology and equipment in a timely manner; regularly maintain and upgrade existing cleaning equipment and tools to ensure their normal operation and cleaning effect.

[0021] The environmental meteorological data of the photovoltaic power station in step 1 includes but is not limited to light, humidity and temperature; the future weather forecast data is the weather forecast information for the next few days; the photovoltaic power station inverter reading data includes but is not limited to the actual power generation, power generation and voltage of the power station; the unattended inspection data of the photovoltaic power station includes but is not limited to the cleanliness and fault information of the photovoltaic power station; The theoretical power generation real-time monitoring model in step 3 is based on the performance data of photovoltaic modules and the meteorological instrument to calculate the theoretical power generation of the current power generation unit in real time according to the theoretical power generation efficiency calculation formula. The theoretical power generation efficiency calculation formula is: Theoretical maximum power generation (kWh) = photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency, where photovoltaic panel area: is the area of ​​each photovoltaic module; Light intensity: Calculate the light intensity of the photovoltaic power station at different time periods based on the data collected in real time by the meteorological instrument and future weather forecast data; Photovoltaic module conversion efficiency: Determine the rated efficiency of the photovoltaic module based on the photovoltaic module brand and theoretical data; The cleaning cycle optimization model is based on the comparison of actual power generation and theoretical power generation data to form an intuitive comparison curve and provide optimal cleaning cycle and cleaning strategy recommendations.

[0022] The theoretical power generation prediction model is based on the performance data of photovoltaic modules, meteorological data and weather forecast data. The power generation prediction model is established to predict the theoretical power generation in the future and refresh it at intervals. The calculation formula for the predicted theoretical power generation efficiency is predicted theoretical power generation = k × theoretical maximum power generation, that is, predicted theoretical power generation (kWh) = k × photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency. In the formula, k is the cleaning constant. The cleaning constant k is related to but not limited to the cleaning frequency, method, intensity, photovoltaic module performance data, meteorological data and weather forecast data.

[0023] The contents of the cleaning plan optimization and adjustment in step seven include but are not limited to the cleaning frequency, optimization of cleaning routes and the number of cleaning equipment.

[0024] Compared with the prior art, the method and system for generating clean demand based on power generation parameters have the following advantages: Through the cooperation of the visual inspection mechanism and the walking frame mechanism, the device can be driven to move stably on different ground surfaces to clean photovoltaic panels and plan cleaning routes; the visual inspection mechanism avoids a large amount of manual inspection and maintenance work, thereby saving labor costs; The height and inclination of the triangular frame can be stably adjusted through the walking frame mechanism to match the inclination angle of the photovoltaic panel; The cleaning mechanism can be adjusted to match the tilt angle of the photovoltaic panel, and the photovoltaic panel can be brushed, vacuumed, sprayed, wiped (dried), and dried in sequence to ensure the cleaning requirements of the photovoltaic panel; The dust thickness monitoring mechanism monitors the dust thickness of the solar photovoltaic panels before and after cleaning to obtain the degree of cleanliness, and the weather detector is used for real-time weather of the solar photovoltaic station; The data processing subsystem pre-processes the data collected in the database. The data modeling subsystem performs power generation modeling based on the processed data and analysis results, and establishes a theoretical power generation prediction model, a theoretical power generation real-time monitoring model and a cleaning cycle optimization model. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the results of the cleaning demand judgment. The cleaning feedback subsystem optimizes and adjusts the cleaning demand judgment model and the cleaning plan based on the feedback on the cleaning effect, thereby improving the power generation efficiency of the photovoltaic power station, maximizing the use of cleaning resources and reducing cleaning costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a front view structural schematic diagram of the system equipment in the present invention.

[0026] Figure 2 It is a three-dimensional structural schematic diagram of the system equipment in the present invention.

[0027] Figure 3It is a three-dimensional structural schematic diagram of the visual inspection mechanism in the present invention.

[0028] Figure 4 It is a front view structural schematic diagram of the dust thickness monitoring mechanism and the cleaning mechanism in the present invention.

[0029] Figure 5 It is a schematic diagram of the upper three-dimensional structure of the dust thickness monitoring mechanism and the cleaning mechanism in the present invention.

[0030] Figure 6 It is a schematic diagram of the bottom three-dimensional structure of the dust thickness monitoring mechanism and the cleaning mechanism in the present invention.

[0031] Figure 7 It is a schematic diagram of the system triangle framework of the present invention.

[0032] Figure 8 It is a schematic diagram of the generation method of the present invention.

[0033] Fig. 9 It is the calculation table of the cleaning constant k value of the present invention.

[0034] In the figure, 1. walking frame mechanism; 2. visual sensor; 3. visual camera; 4. water spray assembly; 5. meteorological detector; 6. hot air assembly; 7. dust collection box; 8. dust brush spray assembly; 9. water absorption roller; 10. infrared sensor; 11. hot air exhaust box; 12. laser sensor; 13. adjustment assembly; 14. water tank; 15. hot air box; 16. fan; 17. triangular frame; 18. articulated seat; 19. telescopic electric push rod; 20. rotating plate ; 21. Motor rotation seat; 22. Shock-absorbing spring rod; 23. Telescopic sleeve rod; 24. Double-axis motor seat; 25. Moving wheel; 26. Swing electric push rod; 27. Mounting base plate; 28. Articulated connecting rod; 29. ​​Rotating motor seat; 30. Mounting frame; 31. Dust removal hood; 32. Dust brush roller; 33. Power motor; 34. Air guide duct; 35. Water suction roller; 36. Dust suction duct; 37. Spray pipe; 38. Water injection pipe; 39. Water pump; 40. Connecting seat. DETAILED DESCRIPTION

[0035] The following are specific embodiments of the present invention and the accompanying drawings to further describe the technical solution of the present invention, but the present invention is not limited to these embodiments.

[0036] like Figure 1-Figure 7As shown, the cleaning demand generation system based on power generation parameters includes a cleaning system pan / tilt, a meteorological detector 5, a visual inspection mechanism, a dust thickness monitoring mechanism, a cleaning mechanism, a walking frame mechanism and an electric control box. The meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the electric control box are all arranged on the walking frame mechanism. A battery and a main control machine are arranged inside the electric control box. The main control machine is electrically connected to the cleaning system pan / tilt, the battery, the meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the walking frame mechanism respectively. The main control machine is provided with a data processing subsystem, a data modeling subsystem, a cleaning plan formulation subsystem and a cleaning feedback subsystem. The cleaning system pan / tilt is electrically connected to the terminal device, the third-party weather data interface, the API data interface of the charging station and the inverter data collection interface respectively.

[0037] The walking frame mechanism drives the meteorological detector, the visual inspection mechanism, the dust thickness monitoring mechanism, the cleaning mechanism and the electric control box to move. The visual inspection mechanism accurately monitors the solar photovoltaic panels and the ground where the solar photovoltaic panels are located. The walking frame mechanism is controlled to walk on both sides of the solar photovoltaic panels. The cleaning mechanism cleans the solar photovoltaic panels. During the cleaning process, the dust thickness monitoring mechanism monitors the dust thickness of the solar photovoltaic panels before and after cleaning to obtain the degree of cleanliness. The meteorological detector 5 is used for real-time meteorology of the solar photovoltaic station. The terminal device can receive information in real time and remotely control related equipment. The third-party weather data interface integrates the weather forecast data source to obtain weather forecast information for the next few days. The API data interface of the charging station and the inverter data acquisition interface obtain the power generation power, voltage and other data of the power station in real time. The data processing subsystem preprocesses the data collected in the database. The data modeling subsystem performs power generation modeling based on the processed data and analysis results. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the results of the cleaning demand judgment. The cleaning feedback subsystem optimizes and adjusts the cleaning demand judgment model and the cleaning plan based on the feedback of the cleaning effect.

[0038] The triangular frame walking adjustment subsystem includes a triangular frame 17, and the four corners of the lower end of the triangular frame 17 are fixed with hinged seats, and the lower ends of the hinged seats are fixed with telescopic electric push rods 19, and the lower ends of the telescopic electric push rods 19 are fixed with rotating plates 20. The lower end of the rotating plate 20 is rotatably provided with a motor rotation seat 21, and the motor output shaft of the motor rotation seat 21 is fixedly connected to the rotating plate 20. The lower end of the motor rotation seat 21 is provided with a shock-absorbing spring rod 22 and four telescopic sleeve rods 23, and the lower ends of a shock-absorbing spring rod 22 and four telescopic sleeve rods 23 are provided with a double-axis motor seat 24, and moving wheels 25 are fixed on the motor output shafts at both ends of the double-axis motor seat 24. A connecting seat 40 is fixed between the two telescopic electric push rods 19 on the same side, and the meteorological detector 5 is fixed to the middle of the upper end of the triangular frame 17, and the electric control box is arranged on the triangular frame 17.

[0039] The two telescopic electric push rods 19 on both sides cooperate with the connecting seat 40, and the articulated seat cooperates with the telescopic electric push rod 19 to adjust the height and inclination of the triangular frame 17 to match the inclination angle of the photovoltaic panel. Each telescopic electric push rod 19 can be raised and lowered individually to ensure that the device matches the concave and convex shape of the ground when moving, and ensure that the height and inclination of the triangular frame 17 remain unchanged. The motor output shafts at both ends of the dual-axis motor seat 24 drive the moving wheels 25 to rotate for walking. A shock-absorbing spring rod 22 and four telescopic sleeve rods 23 cooperate to stabilize the motor rotation seat 21 and the dual-axis motor seat 24 to avoid strong shaking. The motor output shaft of the motor rotation seat 21 drives the rotating plate 20 to rotate, thereby driving the dual-axis motor seat 24 to rotate. The four motor rotation seats 21 cooperate to enable the device to turn and move.

[0040] The visual inspection mechanism includes a plurality of visual sensors and a plurality of visual cameras 3 . The plurality of visual sensors are fixed on the dual-axis motor base 24 at corresponding positions, and the visual cameras 3 are fixed on the four upper corners of the triangular frame 17 .

[0041] A number of visual sensors and a number of visual cameras 3 are used together for inspection to collect fault information of the photovoltaic power station and data such as the concave and convex shape of the ground of the photovoltaic station, so as to facilitate mobile inspection.

[0042] The cleaning mechanism includes a water spray assembly 4, a hot air assembly 6, a dust box 7 and a positioning assembly 13. The water spray assembly 4, the hot air assembly 6 and the dust box 7 are arranged at the upper end of the triangular frame 17. The positioning assembly 13 is arranged in the middle of the lower end of the triangular frame 17. The lower end of the positioning assembly 13 is provided with a water absorption roller 9, the front side of the water absorption roller 9 is provided with a dust brushing spray assembly 8, and the rear side of the water absorption roller 9 is provided with a hot air exhaust box 11.

[0043] The positioning component 13 adjusts the angles of the dust brushing spray component 8, the water absorption roller component 9 and the hot air exhaust box 11 to match the inclined photovoltaic panel. The dust brushing spray component 8 brushes the photovoltaic panel, and the brushed dust is absorbed by the hot air component 6 and the dust collecting box 7, and is adsorbed inside the dust collecting box 7 for regular and quantitative treatment. The water spray component 4 is injected with water and cooperates with the dust brushing spray component 8 to spray and clean the photovoltaic panel after dust brushing. The water absorption roller component 9 absorbs water and wipes the cleaned photovoltaic panel. The hot air component 6 and the hot air exhaust box 11 cooperate to dry the photovoltaic panel after wiping.

[0044] The water spray assembly 4 includes a water tank 14 and a water pump 39, both of which are fixed at the upper end of the triangular frame 17, and the water inlet end of the water pump 39 is connected to the water tank 14 through a pipeline; the hot air assembly 6 includes a hot air box 15 and a fan 16, both of which are fixed at the upper end of the triangular frame 17, and the air outlet end of the fan 16 is connected to the air inlet end of the hot air box 15 through a pipeline, and the air inlet end of the fan 16 is connected to the air outlet end of the dust collecting box 7 The ends are connected by pipes; the positioning component 13 includes a mounting base 27, the mounting base 27 is fixed to the middle part of the lower end of the triangular frame 17, the lower end of the mounting base 27 is hinged with a swing electric push rod 26 and a hinged connecting rod 28, the end of the swing electric push rod 26 is hinged on the hinged connecting rod 28, the lower end of the hinged connecting rod 28 is fixed with a rotating motor seat 29, and the motor output shaft of the rotating motor seat 29 is fixed with a mounting frame 30; the water-absorbing roller member 9 includes a water-absorbing roller cover, the water-absorbing roller cover is fixed to the lower end of the mounting frame 30, and a water-absorbing roller 35 is rotatably arranged inside the water-absorbing roller cover; the dust-brushing spraying component 8 includes a dust-removing cover 31, the dust-removing cover 31 is fixed to the front side of the water-absorbing roller cover, a dust-absorbing pipe 36 is arranged inside the front side of the dust-removing cover 31, the dust-absorbing pipe 36 is connected to the air inlet end of the dust-collecting box 7 by a pipe, a dust-brushing roller 32 is rotatably arranged in the middle position inside the dust-removing cover 31, a spray pipe 37 is arranged on the rear side of the dust-removing cover 31, and a spray pipe A water injection pipe 38 is connected to 37, and the water injection pipe 38 extends out of the dust removal cover 31, and the water injection pipe 38 is connected to the water outlet end of the water pump 39 through a pipeline; a power motor 33 is fixed to the side of the dust removal cover 31, and the output shaft of the power motor 33 is transmission-connected to the rotating shaft of the dust brush roller 32 and the rotating shaft of the water suction roller 35; the upper end of the hot air discharge box 11 is provided with an air duct 34 connected thereto, and the air duct 34 is connected to the air outlet end of the hot air box 15 through a pipeline.

[0045] The electric push rod 26 is extended and retracted to drive the hinged connecting rod 28 to be raised or swung down, and the hinged connecting rod 28 drives the rotating motor seat 29 to be raised or swung down, so as to adjust the angles of the dust brushing spray assembly 8, the water absorption roller 9 and the hot air discharge box 11 to match the inclined photovoltaic panel; the output shaft of the power motor 33 drives the dust brushing roller 32 to rotate, and the dust brushing roller 32 brushes the dust on the photovoltaic panel to the dust suction pipe 36, and the dust suction pipe 36 is connected to the air inlet end of the dust collecting box 7 through a pipe, and the fan 16 sucks air, so that the inside of the dust collecting box 7 is shaped A negative pressure is formed to suck the brushed dust into the dust collecting box 7 for regular and quantitative treatment; the water pump 39 injects the clean water in the water tank 14 into the spray pipe 37 through the pipeline via the water injection pipe 38, and sprays and cleans the photovoltaic panels after brushing; the output shaft of the power motor 33 drives the water absorption roller 35 to rotate, and absorbs water and wipes the cleaned photovoltaic panels; the fan 16 blows cold air into the hot air box 15 to form hot air, and the hot air is injected into the hot air discharge box 11 through the air guide duct 34, blows on the photovoltaic panels, and dries the photovoltaic panels after wiping.

[0046] The dust thickness monitoring mechanism includes a plurality of infrared sensors 10 and a plurality of laser sensors 12 , which are alternately fixed on the front side of the dust removal cover 31 and the rear side of the hot air exhaust box 11 .

[0047] A plurality of infrared sensors 10 and a plurality of laser sensors 12 cooperate to monitor the solar photovoltaic panels before and after cleaning to obtain dust thickness data.

[0048] The data processing subsystem preprocesses the collected data. The preprocessing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, conduct in-depth mining and analysis of power generation parameters, and find out the characteristic information related to cleaning needs. The data modeling subsystem performs power generation modeling based on the processed data and analysis results. The model includes but is not limited to theoretical power generation prediction model, theoretical power generation real-time monitoring model and cleaning cycle optimization model. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the model and the recommendations of the decision support system. The cleaning plan should include but not be limited to the time, method, intensity, execution frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. The cleaning feedback subsystem performs cleaning operations according to the cleaning plan. After the cleaning operation is completed, the power generation parameters of the photovoltaic modules are monitored again to evaluate the cleaning effect; based on the feedback on the cleaning effect, the cleaning demand judgment model and the cleaning plan are optimized and adjusted.

[0049] like Figure 8 As shown, the method for generating clean demand based on power generation parameters includes the following generation steps: Step 1, preliminary preparation: installing generation equipment in the photovoltaic power station, establishing a database for storing real-time monitored power generation parameter data and weather condition data, collecting photovoltaic module brand data and laboratory theoretical data, and determining the rated efficiency of the photovoltaic module; Step 2, data collection and transmission: collect various data in real time, including but not limited to dust thickness, PV power station environmental meteorological data, future weather forecast data, PV power station inverter reading data and PV power station unattended inspection data, and transmit the collected data to the database in real time; Step 3: Data processing and analysis: pre-process the data collected in the database. The pre-processing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, conduct in-depth mining and analysis of power generation parameters, analyze the correlation between power generation parameters and cleaning requirements, and find out the characteristic information that affects cleaning requirements; Step 4: Data modeling: Based on the processed data and analysis results, power generation modeling is performed, and the model includes but is not limited to a theoretical power generation prediction model, a theoretical power generation real-time monitoring model, and a cleaning cycle optimization model; Step 5: Cleaning demand judgment: Use the established cleaning demand judgment model to judge the power generation parameter data monitored in real time, and determine whether cleaning is needed and the priority of cleaning based on the judgment results; Step 6: Formulate a cleaning plan: Develop a cleaning optimization plan based on the results of the cleaning needs assessment. The cleaning plan should include but not be limited to the time, method, intensity, frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. Step 7: Cleaning operation execution and feedback: Execute the cleaning operation according to the cleaning plan. After the cleaning operation is completed, monitor the power generation parameters of the PV modules again to evaluate the cleaning effect. According to the feedback of the cleaning effect, optimize and adjust the cleaning demand judgment model and the cleaning plan. Step 8: Cleaning technology and equipment upgrade: Pay attention to the latest developments in photovoltaic cleaning technology, introduce and apply advanced cleaning technology and equipment in a timely manner; regularly maintain and upgrade existing cleaning equipment and tools to ensure their normal operation and cleaning effect.

[0050] The PV power station environmental meteorological data in step 1 include but are not limited to light, humidity and temperature; the future weather forecast data are weather forecast information for the next few days; the PV power station inverter reading data include but are not limited to the actual power generation, power generation and voltage of the power station; the unattended inspection data of the PV power station include but are not limited to the cleanliness and fault information of the PV power station; The theoretical power generation real-time monitoring model in step 3 is based on the performance data of photovoltaic modules. The meteorological instrument calculates the theoretical power generation of the current power generation unit in real time according to the theoretical power generation efficiency calculation formula. The theoretical power generation efficiency calculation formula is: Theoretical maximum power generation (kWh) = photovoltaic panel area (m²) X light intensity (kW / m²) X light exposure time (h) X photovoltaic module conversion efficiency, where photovoltaic panel area: is the area of ​​each photovoltaic module; Light intensity: Calculate the light intensity of the photovoltaic power station at different time periods based on the data collected in real time by the meteorological instrument and future weather forecast data; Photovoltaic module conversion efficiency: Determine the rated efficiency of the photovoltaic module based on the photovoltaic module brand and theoretical data; The cleaning cycle optimization model is based on the comparison of actual power generation and theoretical power generation data to form an intuitive comparison curve and provide optimal cleaning cycle and cleaning strategy recommendations.

[0051] The theoretical power generation prediction model is based on the performance data of photovoltaic modules, meteorological data and weather forecast data. The power generation prediction model is established to predict the theoretical power generation in the future and refresh it at intervals. The calculation formula for the predicted theoretical power generation efficiency is predicted theoretical power generation = k × theoretical maximum power generation, that is, predicted theoretical power generation (kWh) = k × photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency. In the formula, k is the cleaning constant. The cleaning constant k is related to but not limited to the cleaning frequency, method, intensity, photovoltaic module performance data, meteorological data and weather forecast data.

[0052] The contents to be optimized and adjusted in the cleaning plan in step seven include but are not limited to the cleaning frequency, optimization of cleaning routes and the number of cleaning equipment.

[0053] Working principle of the present invention: Preliminary preparation: Install generation equipment in the photovoltaic power station, establish a database for storing the real-time monitored power generation parameter data and weather condition data, collect photovoltaic module brand data and laboratory theoretical data, and determine the rated efficiency of the photovoltaic module; Data collection and transmission: Real-time collection of various data, including but not limited to dust thickness, PV power station environmental meteorological data, future weather forecast data, PV power station inverter reading data and PV power station unattended inspection data, and real-time transmission of the collected data to the database; That is, the two telescopic electric push rods 19 on both sides cooperate with the connecting seat 40, and the articulated seat cooperates with the telescopic electric push rods 19 to adjust the height and inclination of the triangular frame 17 to match the inclination angle of the photovoltaic panel. Each telescopic electric push rod 19 can be raised and lowered separately to ensure that the device matches the concave and convex shape of the ground when moving, and ensure that the height and inclination of the triangular frame 17 remain unchanged. The motor output shafts at both ends of the dual-axis motor seat 24 drive the moving wheels 25 to rotate for walking. A shock-absorbing spring rod 22 and four telescopic sleeve rods 23 cooperate to stabilize the motor rotation seat 21 and the dual-axis motor seat 24 to avoid strong shaking. The motor output shaft of the motor rotation seat 21 drives the rotating plate 20 to rotate, thereby driving the dual-axis motor seat 24 to rotate. The four motor rotation seats 21 cooperate to enable the device to turn and move; during the movement, a number of visual sensors and a number of visual cameras 3 are used for inspection to collect fault information of the photovoltaic power station and data such as the concave and convex shape of the photovoltaic station ground, which is convenient for mobile inspection; The electric push rod 26 is extended and retracted to drive the hinged connecting rod 28 to be raised or lowered, and the hinged connecting rod 28 drives the rotating motor seat 29 to be raised or lowered, thereby adjusting the angles of the dust brushing spray assembly 8, the water absorption roller 9 and the hot air exhaust box 11 to match the tilted photovoltaic panel; The output shaft of the power motor 33 drives the dust brushing roller 32 to rotate, and the dust brushing roller 32 brushes the dust on the photovoltaic panel to the dust collection pipe 36. The dust collection pipe 36 is connected to the air inlet end of the dust collection box 7 through a pipe. The fan 16 sucks air, so that a negative pressure is formed inside the dust collection box 7, and the brushed dust is sucked into the dust collection box 7 for regular quantitative treatment. The water pump 39 injects the clean water in the water tank 14 into the spray pipe 37 through the pipe via the water injection pipe 38 to spray and clean the photovoltaic panels after being dusted; The output shaft of the power motor 33 drives the water absorption roller 35 to rotate, and absorbs water and wipes the cleaned photovoltaic panel; The fan 16 blows cold air into the hot air box 15 to form hot air. The hot air is injected into the hot air exhaust box 11 through the air guide duct 34 and blows on the photovoltaic panels to dry the photovoltaic panels after being wiped with water. A plurality of infrared sensors 10 and a plurality of laser sensors 12 cooperate to monitor the solar photovoltaic panels before and after cleaning to obtain dust thickness data.

[0054] Data processing and analysis: pre-process the data collected in the database. The pre-processing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, conduct in-depth mining and analysis of power generation parameters, analyze the correlation between power generation parameters and cleaning requirements, and find out the characteristic information that affects cleaning requirements; Data modeling: Based on the processed data and analysis results, power generation modeling is performed, including but not limited to theoretical power generation prediction model, theoretical power generation real-time monitoring model and cleaning cycle optimization model; the theoretical power generation real-time monitoring model is based on the performance data of photovoltaic modules and the meteorological instrument to calculate the theoretical power generation of the current power generation unit in real time according to the theoretical power generation efficiency calculation formula. The theoretical power generation efficiency calculation formula is: theoretical maximum power generation (kWh) = photovoltaic panel area (m²) X light intensity (kW / m²) X light exposure time (h) X photovoltaic module conversion efficiency, where photovoltaic panel area: is the area of ​​each photovoltaic module; Light intensity: Calculate the light intensity of the photovoltaic power station at different time periods based on the data collected in real time by the meteorological instrument and future weather forecast data; Photoperiod (h): average photoperiod duration; Photovoltaic module conversion efficiency: Determine the rated efficiency of the photovoltaic module based on the photovoltaic module brand and theoretical data; The cleaning cycle optimization model is based on the comparison of actual power generation and theoretical power generation data to form an intuitive comparison curve and provide optimal cleaning cycle and cleaning strategy recommendations.

[0055] The theoretical power generation prediction model is based on the performance data of photovoltaic modules, meteorological data and weather forecast data, and the power generation prediction model is established to predict the theoretical power generation in the future and refresh it at intervals; the calculation formula for the predicted theoretical power generation efficiency is predicted theoretical power generation = k × theoretical maximum power generation, that is, predicted theoretical power generation (kWh) = k × photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency, where k is the cleaning constant; Cleaning demand judgment: Use the established cleaning demand judgment model to judge the power generation parameter data monitored in real time, and determine whether cleaning is needed and the cleaning priority based on the judgment results; Cleaning plan formulation: Based on the results of cleaning demand judgment, formulate a cleaning optimization plan. The cleaning plan should include but not be limited to the time, method, intensity, execution frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation; Cleaning operation execution and feedback: Perform cleaning operations according to the cleaning plan. After the cleaning operation is completed, monitor the power generation parameters of the PV modules again to evaluate the cleaning effect. Based on the feedback on the cleaning effect, optimize and adjust the cleaning demand judgment model and cleaning plan. Cleaning technology and equipment upgrades: Pay attention to the latest developments in photovoltaic cleaning technology, introduce and apply advanced cleaning technology and equipment in a timely manner; regularly maintain and upgrade existing cleaning equipment and tools to ensure their normal operation and cleaning effect.

[0056] According to the photovoltaic module brand and theoretical data: The photovoltaic panel area (m²) is 1m², the average light intensity (kW / m²) is 4kwh / m², and the photovoltaic module conversion efficiency is 14.5%; the local light time (h) is 6h; According to the theoretical power generation efficiency calculation formula: Theoretical maximum power generation = 1m²X4kwh / m²X6hX14.5%=3.48kWh. The power generation for seven days is 24.36kWh.

[0057] The relationship between the cleaning frequency and power generation was experimentally studied, and a table was obtained, such as Fig. 9 As shown by Fig. 9 From the experimental data, it can be seen that when the cleaning frequency exceeds 3 times a week, the actual effect is not obvious, and a cleaning constant can be obtained. The theoretical power generation prediction model can be calculated to obtain K, which is about 0.9.

[0058] The calculation formula for predicted theoretical power generation efficiency is predicted theoretical power generation = k × theoretical maximum power generation, that is, predicted theoretical power generation (kWh) = k × photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency, where k is the cleaning constant That is, under this environmental condition, the best cleaning frequency is 3 times a week, which has the highest efficiency. At this time, the cleaning constant K is about 0.9.

[0059] The cleaning constant K is about 0.9, and the theoretical power generation in the future is predicted. The cleaning constant K is refreshed at intervals to continue predicting the theoretical power generation in the future.

[0060] By continuing to monitor the performance data of PV modules, meteorological data and weather forecast data, the cleaning constant K will change and a cleaning demand plan will be generated based on the power generation parameters. In summary, through the cooperation of the visual inspection mechanism and the walking frame mechanism, the device can be driven to move stably on different ground surfaces to clean photovoltaic panels and plan cleaning routes; the visual inspection mechanism avoids a large amount of manual inspection and maintenance work, thereby saving labor costs; The height and inclination of the triangular frame 17 can be stably adjusted through the walking frame mechanism to match the inclination angle of the photovoltaic panel; The cleaning mechanism can be adjusted to match the tilt angle of the photovoltaic panel, and the photovoltaic panel can be brushed, vacuumed, sprayed, wiped (dried), and dried in sequence to ensure the cleaning requirements of the photovoltaic panel; The dust thickness monitoring mechanism monitors the dust thickness of the solar photovoltaic panels before and after cleaning to obtain the degree of cleanliness, and the weather detector 5 is used for the real-time weather of the solar photovoltaic station; The data processing subsystem pre-processes the data collected in the database. The data modeling subsystem performs power generation modeling based on the processed data and analysis results, and establishes a theoretical power generation prediction model, a theoretical power generation real-time monitoring model and a cleaning cycle optimization model. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the results of the cleaning demand judgment. The cleaning feedback subsystem optimizes and adjusts the cleaning demand judgment model and the cleaning plan based on the feedback on the cleaning effect, thereby improving the power generation efficiency of the photovoltaic power station, maximizing the use of cleaning resources and reducing cleaning costs.

[0061] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A cleaning demand generation system based on power generation parameters, comprising a cleaning system platform, a meteorological detector (5), a visual inspection mechanism, a dust thickness monitoring mechanism, a cleaning mechanism, a walking frame mechanism and an electric control box, characterized in that: The meteorological detector, visual inspection mechanism, dust thickness monitoring mechanism, cleaning mechanism and electric control box are all arranged on the walking frame mechanism. A battery and a main control machine are arranged inside the electric control box. The main control machine is electrically connected to the cleaning system pan / tilt, battery, meteorological detector, visual inspection mechanism, dust thickness monitoring mechanism, cleaning mechanism and walking frame mechanism respectively. The main control machine is provided with a data processing subsystem, a data modeling subsystem, a cleaning plan formulation subsystem and a cleaning feedback subsystem. The cleaning system pan / tilt is electrically connected to the terminal device, a third-party weather data interface, an API data interface of the charging station and an inverter data collection interface respectively.

2. A system for generating clean demand based on power generation parameters according to claim 1, characterized in that: The triangular frame walking adjustment subsystem comprises a triangular frame (17), wherein hinge seats are fixed at the four corners of the lower end of the triangular frame (17), telescopic electric push rods (19) are fixed at the lower ends of the hinge seats, and rotating plates (20) are fixed at the lower ends of the telescopic electric push rods (19). A motor rotation seat (21) is rotatably provided at the lower end of the rotating plate (20), and the motor output shaft of the motor rotation seat (21) is fixedly connected to the rotating plate (20). A damping spring rod (22) and four telescopic sleeve rods (23) are provided at the lower end of the motor rotation seat (21), and a double-axis motor seat (24) is provided at the lower ends of the damping spring rod (22) and the four telescopic sleeve rods (23). Moving wheels (25) are fixed on the motor output shafts at both ends of the double-axis motor seat (24), and a connecting seat (40) is fixed between two telescopic electric push rods (19) on the same side. The meteorological detector (5) is fixed at the middle of the upper end of the triangular frame (17), and the electric control box is arranged on the triangular frame (17).

3. A system for generating clean demand based on power generation parameters according to claim 2, characterized in that: The visual inspection mechanism comprises a plurality of visual sensors and a plurality of visual cameras (3), wherein the plurality of visual sensors are fixed on a dual-axis motor base (24) at corresponding positions, and the visual cameras (3) are fixed on the four corners of the upper end of the triangular frame (17).

4. A system for generating clean demand based on power generation parameters according to claim 3, characterized in that: The cleaning mechanism comprises a water spray assembly (4), a hot air assembly (6), a dust collection box (7) and a positioning assembly (13); the water spray assembly (4), the hot air assembly (6) and the dust collection box (7) are arranged at the upper end of a triangular frame (17); the positioning assembly (13) is arranged at the middle of the lower end of the triangular frame (17); a water absorption roller (9) is arranged at the lower end of the positioning assembly (13); a dust brushing spray assembly (8) is arranged at the front side of the water absorption roller (9); and a hot air exhaust box (11) is arranged at the rear side of the water absorption roller (9).

5. A system for generating clean demand based on power generation parameters according to claim 4, characterized in that: The water spray assembly (4) comprises a water tank (14) and a water pump (39), wherein the water tank (14) and the water pump (39) are both fixed to the upper end of the triangular frame (17), and the water inlet end of the water pump (39) is connected to the water tank (14) via a pipeline; The hot air assembly (6) comprises a hot air box (15) and a fan (16), wherein the hot air box (15) and the fan (16) are both fixed to the upper end of the triangular frame (17), the air outlet end of the fan (16) is connected to the air inlet end of the hot air box (15) via a pipeline, and the air inlet end of the fan (16) is connected to the air outlet end of the dust collecting box (7) via a pipeline; The positioning assembly (13) comprises a mounting base (27), the mounting base (27) being fixed to the middle portion of the lower end of the triangular frame (17), the lower end of the mounting base (27) being hinged with a positioning electric push rod (26) and a hinged connecting rod (28), the end of the positioning electric push rod (26) being hinged on the hinged connecting rod (28), the lower end of the hinged connecting rod (28) being fixed with a rotating motor seat (29), and the motor output shaft of the rotating motor seat (29) being fixed with a mounting frame (30); The suction roller member (9) comprises a suction roller cover, which is fixed to the lower end of the mounting frame (30), and a suction roller (35) is rotatably arranged inside the suction roller cover; The dust brushing and spraying assembly (8) comprises a dust removal hood (31), the dust removal hood (31) is fixed to the front side of the water suction roller hood, a dust suction pipe (36) is provided at the front side of the dust removal hood (31), the dust suction pipe (36) is connected to the air inlet end of the dust collection box (7) via a pipe, a dust brushing roller (32) is rotatably provided at the middle position of the dust removal hood (31), a spraying pipe (37) is provided at the rear side of the dust removal hood (31), a water injection pipe (38) is connected to the spraying pipe (37), the water injection pipe (38) extends out of the dust removal hood (31), and the water injection pipe (38) is connected to the water outlet end of the water pump (39) via a pipe; A power motor (33) is fixed to the side of the dust removal cover (31), and the output shaft of the power motor (33) is transmission-connected to the rotating shaft of the dust brushing roller (32) and the rotating shaft of the water absorption roller (35); An air guide duct (34) communicating with the hot air exhaust box (11) is provided at the upper end thereof, and the air guide duct (34) is connected to the air outlet end of the hot air box (15) via a pipeline.

6. A system for generating clean demand based on power generation parameters according to claim 5, characterized in that: The dust thickness monitoring mechanism comprises a plurality of infrared sensors (10) and a plurality of laser sensors (12), wherein the plurality of infrared sensors (10) and the plurality of laser sensors (12) are alternately fixed on the front side of the dust removal cover (31) and the rear side of the hot air exhaust box (11).

7. A system for generating clean demand based on power generation parameters according to claim 6, characterized in that: The data processing subsystem preprocesses the collected data, and the preprocessing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, and deeply mine and analyze the power generation parameters to find out the characteristic information related to the cleaning requirements. The data modeling subsystem performs power generation modeling based on the processed data and analysis results. The model includes but is not limited to a theoretical power generation prediction model, a theoretical power generation real-time monitoring model and a cleaning cycle optimization model. The cleaning plan formulation subsystem formulates a cleaning optimization plan based on the model and the recommendations of the decision support system. The cleaning plan should include but is not limited to the time, method, intensity, execution frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. The cleaning feedback subsystem performs the cleaning operation according to the cleaning plan. After the cleaning operation is completed, the power generation parameters of the photovoltaic components are monitored again to evaluate the cleaning effect; Based on the feedback on cleaning results, the cleaning needs judgment model and cleaning plan are optimized and adjusted.

8. A system method for generating a clean demand based on power generation parameters as claimed in claim 7, characterized in that: The generation steps include: Step 1: Preliminary preparation: Install generation equipment in the PV power station, establish a database to store the real-time monitored power generation parameter data and weather condition data, collect PV module brand data and laboratory theoretical data, and determine the rated efficiency of PV modules; Step 2, data collection and transmission: collect various data in real time, including but not limited to dust thickness, PV power station environmental meteorological data, future weather forecast data, PV power station inverter reading data and PV power station unattended inspection data, and transmit the collected data to the database in real time; Step 3: Data processing and analysis: pre-process the data collected in the database. The pre-processing methods include but are not limited to data cleaning and outlier detection to ensure the accuracy and reliability of the data, conduct in-depth mining and analysis of power generation parameters, analyze the correlation between power generation parameters and cleaning requirements, and find out the characteristic information that affects cleaning requirements; Step 4: Data modeling: Based on the processed data and analysis results, power generation modeling is performed, and the model includes but is not limited to a theoretical power generation prediction model, a theoretical power generation real-time monitoring model, and a cleaning cycle optimization model; Step 5: Cleaning demand judgment: Use the established cleaning demand judgment model to judge the power generation parameter data monitored in real time, and determine whether cleaning is needed and the priority of cleaning based on the judgment results; Step 6: Formulate a cleaning plan: Develop a cleaning optimization plan based on the results of the cleaning needs assessment. The cleaning plan should include but not be limited to the time, method, intensity, frequency and route of cleaning to ensure the effectiveness and efficiency of the cleaning operation. Step 7: Cleaning operation execution and feedback: Perform cleaning operations according to the cleaning plan. After the cleaning operations are completed, monitor the power generation parameters of the PV modules again to evaluate the cleaning effect. Optimize and adjust the cleaning demand judgment model and cleaning plan based on the feedback of cleaning effect; Step 8: Clean technology and equipment upgrade: Pay attention to the latest developments in photovoltaic clean technology, and introduce and apply advanced clean technology and equipment in a timely manner; Regularly maintain and upgrade existing cleaning equipment and tools to ensure their proper operation and cleaning effectiveness.

9. A method for generating clean demand based on power generation parameters according to claim 8, characterized in that: The environmental meteorological data of the photovoltaic power station in step 1 includes but is not limited to light, humidity and temperature; the future weather forecast data is the weather forecast information for the next few days; the photovoltaic power station inverter reading data includes but is not limited to the actual power generation, power generation and voltage of the power station; the unattended inspection data of the photovoltaic power station includes but is not limited to the cleanliness and fault information of the photovoltaic power station; The theoretical power generation real-time monitoring model in step 3 is based on the performance data of photovoltaic modules and the meteorological instrument to calculate the theoretical power generation of the current power generation unit in real time according to the theoretical power generation efficiency calculation formula. The theoretical power generation efficiency calculation formula is: Theoretical maximum power generation (kWh) = photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency, where photovoltaic panel area: is the area of ​​each photovoltaic module; Light intensity: Calculate the light intensity of the photovoltaic power station at different time periods based on the data collected in real time by the meteorological instrument and future weather forecast data; Photovoltaic module conversion efficiency: Determine the rated efficiency of the photovoltaic module based on the photovoltaic module brand and theoretical data; The cleaning cycle optimization model is based on the comparison of actual power generation and theoretical power generation data to form an intuitive comparison curve and provide the best cleaning cycle and cleaning strategy recommendations; The theoretical power generation prediction model is based on the performance data of photovoltaic modules, meteorological data and weather forecast data. The power generation prediction model is established to predict the theoretical power generation in the future and refresh it at intervals. The calculation formula for the predicted theoretical power generation efficiency is predicted theoretical power generation = k × theoretical maximum power generation, that is, predicted theoretical power generation (kWh) = k × photovoltaic panel area (m²) × light intensity (kW / m²) × light exposure time (h) × photovoltaic module conversion efficiency. In the formula, k is the cleaning constant. The cleaning constant k is related to but not limited to the cleaning frequency, method, intensity, photovoltaic module performance data, meteorological data and weather forecast data.

10. A method for generating clean demand based on power generation parameters according to claim 9, characterized in that: The contents of the cleaning plan optimization and adjustment in step seven include but are not limited to the cleaning frequency, optimization of cleaning routes and the number of cleaning equipment.

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