Photovoltaic panel output control method and system

Abstract

The invention relates to the technical field of photovoltaic panel control, and discloses a photovoltaic panel output control method and system, and the method comprises the steps: monitoring the accumulated snow thickness and dust coverage density of the surface of a photovoltaic panel in real time, and calculating the actual power generation amount and power generation efficiency loss; dynamically adjusting the inclination angle of the photovoltaic panel or triggering self-cleaning operation; and calculating the optimal inclination angle of the photovoltaic panel by using an improved particle swarm optimization algorithm. In the prior art, when a photovoltaic panel is covered by accumulated snow or dust, the coverage state cannot be monitored in real time and the inclination angle cannot be dynamically adjusted, and especially under complex weather conditions, the power generation amount is greatly reduced due to low efficiency or too high cleaning energy consumption of a system. Through real-time coverage state monitoring and inclination angle dynamic adjustment based on particle swarm optimization, efficient output control of the photovoltaic panel inclination angle control motor is realized, so that the problems that the power generation efficiency is influenced by coverings and the cleaning energy consumption is too large are avoided, and the energy utilization rate of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic panel control, and in particular relates to a photovoltaic panel output control method and system. Background Art

[0002] At present, photovoltaic power generation technology faces technical deficiencies in large-scale applications due to covering objects, such as snow and dust, which affect the power generation efficiency. For example, in snowy or windy and sandy environments in winter, snow and dust on the surface of photovoltaic panels will significantly reduce the light transmittance, resulting in a decrease in the power generation efficiency of photovoltaic panels. The existing technology mainly relies on regular cleaning or manual adjustment of the tilt angle, which is time-consuming and labor-intensive, and cannot meet the needs of stable power generation of photovoltaic panels in complex environments in terms of real-time and efficiency. The existing technology also lacks real-time monitoring and intelligent response mechanisms for coverage status. For example, it is impossible to obtain snow and dust coverage status data in real time through sensors, and it is difficult to dynamically adjust the tilt angle of photovoltaic panels or trigger cleaning equipment. Therefore, there is an urgent need for a control method and system that can maximize the utilization of photovoltaic panel output through real-time monitoring and intelligent adjustment in complex environments, such as snow cover and sandstorm weather, so as to improve energy utilization efficiency, reduce maintenance costs, and ensure the long-term stability of photovoltaic power generation. Summary of the invention

[0003] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to propose a photovoltaic panel output control method, aiming to solve the technical problem in the prior art that photovoltaic panels are unable to monitor the coverage status in real time and dynamically adjust the inclination angle when covered with snow or dust, especially under complex weather conditions, and the system's power generation is greatly reduced due to low efficiency or excessive cleaning energy consumption.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a photovoltaic panel output control method, The photovoltaic panel output control method comprises: Step S10: The multi-source sensor installed on the surface of the photovoltaic panel collects the coverage status data of the photovoltaic panel surface in real time. The coverage status data includes the real-time surface optical reflectivity, the real-time surface optical transmittance and the real-time surface light intensity, and the snow thickness is calculated based on the surface coverage status data. and dust coverage density ; Step S20: Calculate theoretical power generation based on real-time surface light intensity , and combined with the snow thickness calculated in step S10 and dust coverage density Calculate actual power generation and power generation efficiency loss ; Step S30: Preset a first power generation efficiency loss threshold and the second power generation efficiency loss threshold ,like and , then the monitoring state is maintained; otherwise, the photovoltaic panel tilt angle pre-adjustment instruction and the photovoltaic panel self-cleaning pre-instruction are sent; Step S40: Calculate the energy consumption of angle adjustment , ,in, is the energy consumption coefficient adjusted per unit angle, is the adjustment amount of the tilt angle, which is determined according to the photovoltaic panel tilt angle pre-adjustment instruction; calculate the self-cleaning energy consumption , ,in, The power required for self-cleaning, is the self-cleaning cleaning time, obtained from the photovoltaic panel self-cleaning pre-instruction; calculate the comprehensive cleaning energy consumption , ; Calculating the optimal tilt angle of photovoltaic panels by improving particle swarm optimization algorithm , specifically including: The tilt angle at time t As a tilted particle, and the size is The tilt angle particle swarm is initialized, and the position is set to and speed is set to ;

[0005] in, is the preset minimum tilt angle of the photovoltaic panel, is the maximum tilt angle of the preset photovoltaic panel, is a random number; The updated speed of the particle with the i+1th tilt angle ,in, is the velocity inertia weight of the particle at the tilt angle, is the optimal position of the particle itself at the tilt angle, is the global optimal position of the particle swarm with tilt angle, is a random number, and is the learning factor, which is used to approach the particle’s own optimal position and the global optimal position; The updated position of the particle with the i+1th tilt angle = + ,in Update the scaling factor for the tilt angle particles to adjust the velocity's influence range and unify the units; set the optimization objective function F( )=max( - ), continuous iteration During the iteration, the velocity inertia weight of the tilted particle is dynamically adjusted with the number of iterations, and the output is optimized to achieve the objective function F( ) Maximum optimal tilt angle ; Step S50: Adjust the servo motor control parameters of the photovoltaic panel to control the tilt angle, and adjust the tilt angle to the optimal tilt angle. .

[0006] Preferably, the snow thickness The calculation formula is:

[0007] in, is the real-time surface optical reflectivity; are snow-related parameters calibrated according to experimental data.

[0008] Preferably, the dust coverage density The calculation formula is:

[0009] in, is the real-time surface optical transmittance, are dust-related parameters calibrated according to experimental data.

[0010] Preferably, the theoretical power generation The calculation formula is:

[0011] in, is the photoelectric conversion efficiency of the photovoltaic panel, which is determined according to the material characteristics of the photovoltaic panel; is the real-time surface illumination intensity; is the surface area of ​​the photovoltaic panel.

[0012] Preferably, in step S40, the velocity inertia weight of the tilt angle particle is dynamically adjusted with the number of iterations during the iteration process, and the formula is: = ,in, is the current iteration number.

[0013] Preferably, in step S20, the power generation efficiency loss function The calculation formula is ,in, Snow thickness and dust coverage density The proportional coefficient of loss in power generation efficiency.

[0014] Preferably, in step S20, the actual power generation The calculation formula is .

[0015] The present invention also provides a photovoltaic panel output control system comprising: The coverage status monitoring module is used to collect the coverage status data of the photovoltaic panel surface in real time through the multi-source sensors installed on the photovoltaic panel surface. The coverage status data includes real-time surface optical reflectivity, real-time surface optical transmittance and real-time surface light intensity, and calculate the snow thickness based on the surface coverage status data. and dust coverage density ; Power generation and efficiency calculation module, used to calculate theoretical power generation based on real-time surface light intensity , and combined with the snow thickness calculated in step S10 and dust coverage density Calculate actual power generation and power generation efficiency loss ; Dynamic response judgment module, used to preset the first power generation efficiency loss threshold and the second power generation efficiency loss threshold ,like and , then the monitoring state is maintained; otherwise, the photovoltaic panel tilt angle pre-adjustment instruction and the photovoltaic panel self-cleaning pre-instruction are sent; Tilt angle optimization module, used to calculate the energy consumption of angle adjustment , ,in, is the energy consumption coefficient adjusted per unit angle, is the adjustment amount of the tilt angle, which is determined according to the photovoltaic panel tilt angle pre-adjustment instruction; calculate the self-cleaning energy consumption , ,in, The power required for self-cleaning, is the self-cleaning cleaning time, obtained from the photovoltaic panel self-cleaning pre-instruction; calculate the comprehensive cleaning energy consumption , ; Calculating the optimal tilt angle of photovoltaic panels by improving particle swarm optimization algorithm , specifically including: The tilt angle at time t As a tilted particle, and the size is The tilt angle particle swarm is initialized, and the position is set to and speed is set to ;

[0016] in, is the preset minimum tilt angle of the photovoltaic panel, is the maximum tilt angle of the preset photovoltaic panel, is a random number; The updated speed of the particle with the i+1th tilt angle ,in, is the velocity inertia weight of the particle at the tilt angle, is the optimal position of the particle itself at the tilt angle, is the global optimal position of the particle swarm with tilt angle, is a random number, and is the learning factor, which is used to approach the particle’s own optimal position and the global optimal position; The updated position of the particle with the i+1th tilt angle = + ,in Update the scaling factor for the tilt angle particles to adjust the velocity's influence range and unify the units; set the optimization objective function F( )=max( - ), continuous iteration During the iteration, the velocity inertia weight of the tilted particle is dynamically adjusted with the number of iterations, and the output is optimized to achieve the objective function F( ) Maximum optimal tilt angle ; The tilt angle adjustment module is used to adjust the servo motor control parameters of the photovoltaic panel to control the tilt angle and adjust the tilt angle to the optimal tilt angle. .

[0017] The present invention also provides a computer program product, including a photovoltaic panel output control program, and the photovoltaic panel output control program implements the photovoltaic panel output control method when executed by a processor.

[0018] The beneficial effect of the present invention is that compared with the prior art, when photovoltaic panels are covered with snow or dust, it is impossible to monitor the coverage status in real time and dynamically adjust the tilt angle, especially under complex weather conditions, and the system suffers from a technical problem of a substantial drop in power generation due to low efficiency or excessive cleaning energy consumption. The present application realizes efficient output control of the photovoltaic panel tilt angle control motor through real-time coverage status monitoring and dynamic adjustment of the tilt angle based on particle swarm optimization, thereby avoiding the problem of covering materials affecting power generation efficiency and excessive cleaning energy consumption, and improving the energy utilization of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a flow chart of a first embodiment of a photovoltaic panel output control method of the present invention.

[0021] Figure 2 The device schematic diagram of a photovoltaic panel output control method of the present invention. DETAILED DESCRIPTION

[0022] 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.

[0023] Embodiment 1: Figure 1 , which is a flow chart of the first embodiment of the photovoltaic panel output control method of the present invention, proposes the first embodiment of the photovoltaic panel output control method of the present invention.

[0024] In a first embodiment, the photovoltaic panel output control method includes: Step S10: The multi-source sensor installed on the surface of the photovoltaic panel collects the coverage status data of the photovoltaic panel surface in real time. The coverage status data includes the real-time surface optical reflectivity, the real-time surface optical transmittance and the real-time surface light intensity, and the snow thickness is calculated based on the surface coverage status data. and dust coverage density ; In order to better evaluate the coverage status of the photovoltaic panel surface in real time, this step realizes dynamic data collection and status calculation based on multi-source sensors, and has the following technical effects: Real-time: Through the collaborative work of multi-source sensors, it is possible to quickly capture changes in surface conditions in the early stages of snow or dust coverage, thus avoiding the decrease in power generation efficiency caused by long-term accumulation of snow or dust.

[0025] High precision: The combined analysis of reflectivity and transmittance data greatly improves the detection accuracy of snow and dust coverage status, ensuring accurate calculation results.

[0026] Comprehensive: Not only limited to monitoring a single cover, but also able to assess snow thickness at the same time and dust covered , providing comprehensive support for subsequent dynamic responses.

[0027] Intelligence: By combining the real-time light intensity I of the photovoltaic panels, the calculated data provides a reliable basis for the subsequent evaluation of power generation efficiency and intelligent decision-making of control strategies.

[0028] Step S20: Calculate theoretical power generation based on real-time surface light intensity , and combined with the snow thickness calculated in step S10 and dust coverage density Calculate actual power generation and power generation efficiency loss ; It should be noted that the power generation efficiency loss function The calculation formula is ,in, Snow thickness and dust coverage density Proportional coefficient of loss of power generation efficiency; actual power generation The calculation formula is ; It is understandable that the power generation efficiency loss function The value of reflects the combined impact of snow and dust cover on power generation efficiency. The actual power generation is calculated by comprehensively considering the theoretical power generation and efficiency loss function to dynamically evaluate the power generation capacity of photovoltaic panels under different environmental conditions.

[0029] It should be understood that in order to better evaluate the actual impact of the covering on power generation efficiency, the technical effects of this step include: real-time calculation of power generation efficiency loss and actual power generation based on real-time data to ensure that the evaluation results are timely and accurate; through the efficiency loss function, the cost of complex calculations is reduced and the calculation speed is improved.

[0030] For example, the area of ​​photovoltaic panels , photoelectric conversion efficiency , real-time light intensity Snow thickness cm, dust coverage density parameter ; Calculate theoretical power generation , calculation efficiency loss function , calculate the actual power generation .

[0031] Step S30: Preset a first power generation efficiency loss threshold and the second power generation efficiency loss threshold ,like and , then the monitoring state is maintained; otherwise, the photovoltaic panel tilt angle pre-adjustment instruction and the photovoltaic panel self-cleaning pre-instruction are sent; It should be noted that if and , indicating that the covering has little impact on the power generation efficiency, and the photovoltaic panels can continue to maintain the current state and only need to be re-monitored regularly; otherwise, it indicates that the covering has a greater impact and it is necessary to trigger the cleaning equipment and adjust the inclination to restore the power generation efficiency.

[0032] It should be understood that in order to better improve the operating efficiency and intelligence level of the system, the unique effects of this step include: through threshold grading, the frequency of cleaning equipment and inclination adjustment is reduced, and the energy consumption of system operation is reduced; after monitoring efficiency loss, it can quickly determine whether cleaning or adjustment operations need to be triggered, ensuring the dynamic response speed of the system.

[0033] Step S40: Calculate the energy consumption of angle adjustment , ,in, is the energy consumption coefficient adjusted per unit angle, is the adjustment amount of the tilt angle, which is determined according to the photovoltaic panel tilt angle pre-adjustment instruction; calculate the self-cleaning energy consumption , ,in, The power required for self-cleaning, is the self-cleaning cleaning time, obtained from the photovoltaic panel self-cleaning pre-instruction; calculate the comprehensive cleaning energy consumption , ; Calculating the optimal tilt angle of photovoltaic panels by improving particle swarm optimization algorithm , specifically including: The tilt angle at time t As a tilted particle, and the size is The tilt angle particle swarm is initialized, and the position is set to and speed is set to ;

[0034] in, is the preset minimum tilt angle of the photovoltaic panel, is the maximum tilt angle of the preset photovoltaic panel, is a random number; The updated speed of the particle with the i+1th tilt angle ,in, is the velocity inertia weight of the particle at the tilt angle, is the optimal position of the particle itself at the tilt angle, is the global optimal position of the particle swarm with tilt angle, is a random number, and is the learning factor, which is used to approach the particle’s own optimal position and the global optimal position; The updated position of the particle with the i+1th tilt angle = + ,in Update the scaling factor for the tilt angle particles to adjust the velocity's influence range and unify the units; set the optimization objective function F( )=max( - ), continuous iteration During the iteration, the velocity inertia weight of the tilted particle is dynamically adjusted with the number of iterations, and the output is optimized to achieve the objective function F( ) Maximum optimal tilt angle ; It is understandable that the particle swarm optimization algorithm dynamically adjusts the position and speed of particles through the combination of global and local search, gradually converges to the global optimal solution, directly reflects the trade-off between power generation efficiency and operating cost, and provides a basis for the intelligent control of photovoltaic panels.

[0035] It should be understood that the technical effects of this step include: intelligence, the particle swarm optimization algorithm realizes the rapid search for the optimal inclination angle, greatly improving the response efficiency of the system; dynamics, by adjusting the inertia weight and particle speed in real time, the adaptability of the algorithm is enhanced; efficiency maximization, combining the inclination angle to adjust the energy consumption and self-cleaning energy consumption, ensuring the maximum power generation efficiency at the lowest operating cost.

[0036] For example, , , the initial particle position ,speed s, , , , , , speed update: , location update: , objective function calculation: Assume kW, kWh, then After multiple iterations, the optimal inclination angle is finally output

[0037] Step S50: Adjust the servo motor control parameters of the photovoltaic panel to control the tilt angle, and adjust the tilt angle to the optimal tilt angle. .

[0038] It should be noted that the output parameters of the transfer machine directly control the electric actuator of the photovoltaic panel, such as a servo motor or a hydraulic system, according to the optimal tilt angle obtained by optimization. Accurately adjust the inclination angle of the photovoltaic panel. After the adjustment is completed, the actual inclination angle is detected by the angle sensor and compared with the optimal inclination angle. Compare and if there is any deviation, send the correction instruction again to ensure the adjustment accuracy.

[0039] In addition, the photovoltaic panel output control system provided by the present invention adopts a photovoltaic panel output control method in the above embodiment, which can solve a technical problem of photovoltaic panel output control. Compared with the prior art, the beneficial effects of the photovoltaic panel output control system provided by the present invention are the same as the beneficial effects of the photovoltaic panel output control method provided by the above embodiment, and the other technical features in the photovoltaic panel output control system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0040] The present invention provides a photovoltaic panel output control device, please refer to Figure 2, a photovoltaic panel output control device includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a photovoltaic panel output control method in the above-mentioned embodiment 1. A photovoltaic panel output control device in the embodiment of the present invention may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players: portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. A photovoltaic panel output control device is only an example and should not bring any restrictions on the functions and scope of use of the embodiments of the present invention. A photovoltaic panel output control device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM 1004, various programs and data required for the operation of a photovoltaic panel output control device are also stored. The processing device 1001, ROM 1002, and RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow a photovoltaic panel output control device to communicate with other devices wirelessly or wired to exchange data. Although a photovoltaic panel output control device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0041] The present invention also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the steps of the photovoltaic panel output control method described above are implemented. The computer program product provided by the present invention can solve a technical problem of photovoltaic panel output control. Compared with the prior art, the beneficial effects of the computer program product provided by the present invention are the same as the beneficial effects of the photovoltaic panel output control method provided by the above embodiment, and will not be repeated here.

[0042] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present invention are executed.

[0043] It should be understood that the various parts disclosed in the present invention can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0044] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A photovoltaic panel output control method, characterized in that: Methods include: Step S10: The multi-source sensor installed on the surface of the photovoltaic panel collects the coverage status data of the photovoltaic panel surface in real time. The coverage status data includes the real-time surface optical reflectivity, the real-time surface optical transmittance and the real-time surface light intensity, and the snow thickness is calculated based on the surface coverage status data. and dust coverage density ; Step S20: Calculate theoretical power generation based on real-time surface light intensity , and combined with the snow thickness calculated in step S10 and dust coverage density Calculate actual power generation and power generation efficiency loss ; Step S30: Preset a first power generation efficiency loss threshold and the second power generation efficiency loss threshold ,like and , then the monitoring state is maintained; otherwise, the photovoltaic panel tilt angle pre-adjustment instruction and the photovoltaic panel self-cleaning pre-instruction are sent; Step S40: Calculate the energy consumption of angle adjustment , ,in, is the energy consumption coefficient adjusted per unit angle, is the adjustment amount of the tilt angle, which is determined according to the photovoltaic panel tilt angle pre-adjustment instruction; calculate the self-cleaning energy consumption , ,in, The power required for self-cleaning, is the self-cleaning cleaning time, obtained from the photovoltaic panel self-cleaning pre-instruction; calculate the comprehensive cleaning energy consumption , ; Calculating the optimal tilt angle of photovoltaic panels by improving particle swarm optimization algorithm , specifically including: The tilt angle at time t As a tilted particle, and the size is The tilt angle particle swarm is initialized, and the position is set to and speed is set to ; in, is the preset minimum tilt angle of the photovoltaic panel, is the preset maximum tilt angle of the photovoltaic panel, is a random number; The updated speed of the particle with the i+1th tilt angle ,in, is the velocity inertia weight of the particle at the tilt angle, is the optimal position of the particle itself at the tilt angle, is the global optimal position of the particle swarm with tilt angle, is a random number, and is the learning factor, which is used to approach the particle’s own optimal position and the global optimal position; The updated position of the particle with the i+1th tilt angle = + ,in Update the scaling factor for the tilt angle particles to adjust the velocity's influence range and unify the units; set the optimization objective function F( )=max( - ), continuous iteration During the iteration, the velocity inertia weight of the tilted particle is dynamically adjusted with the number of iterations, and the output is optimized to achieve the objective function F( ) Maximum optimal tilt angle ; Step S50: Adjust the servo motor control parameters of the photovoltaic panel to control the tilt angle, and adjust the tilt angle to the optimal tilt angle. .

2. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S10, the snow thickness The calculation formula is: in, is the real-time surface optical reflectivity; are snow-related parameters calibrated according to experimental data.

3. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S10, the dust coverage density The calculation formula is: in, is the real-time surface optical transmittance, are dust-related parameters calibrated according to experimental data.

4. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S20, the theoretical power generation The calculation formula is: in, is the photoelectric conversion efficiency of the photovoltaic panel, which is determined according to the material characteristics of the photovoltaic panel; is the real-time surface illumination intensity; is the surface area of ​​the photovoltaic panel.

5. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S40, the velocity inertia weight of the tilt angle particle is dynamically adjusted with the number of iterations during the iteration process, and the formula is: = ,in, is the current iteration number.

6. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S20, the power generation efficiency loss function The calculation formula is ,in, Snow thickness and dust coverage density The proportional coefficient of loss in power generation efficiency.

7. A photovoltaic panel output control method as claimed in claim 1, characterized in that: In step S20, the actual power generation The calculation formula is .

8. A photovoltaic panel output control system, characterized in that: The photovoltaic panel output control system comprises: The coverage status monitoring module is used to collect the coverage status data of the photovoltaic panel surface in real time through the multi-source sensors installed on the photovoltaic panel surface. The coverage status data includes real-time surface optical reflectivity, real-time surface optical transmittance and real-time surface light intensity, and calculate the snow thickness based on the surface coverage status data. and dust coverage density ; Power generation and efficiency calculation module, used to calculate theoretical power generation based on real-time surface light intensity , and combined with the snow thickness calculated in step S10 and dust coverage density Calculate actual power generation and power generation efficiency loss ; Dynamic response judgment module, used to preset the first power generation efficiency loss threshold and the second power generation efficiency loss threshold ,like and , then the monitoring state is maintained; otherwise, the photovoltaic panel tilt angle pre-adjustment instruction and the photovoltaic panel self-cleaning pre-instruction are sent; Tilt angle optimization module, used to calculate the energy consumption of angle adjustment , ,in, is the energy consumption coefficient adjusted per unit angle, is the adjustment amount of the tilt angle, which is determined according to the photovoltaic panel tilt angle pre-adjustment instruction; calculate the self-cleaning energy consumption , ,in, The power required for self-cleaning, is the self-cleaning cleaning time, obtained from the photovoltaic panel self-cleaning pre-instruction; calculate the comprehensive cleaning energy consumption , ; Calculating the optimal tilt angle of photovoltaic panels by improving particle swarm optimization algorithm , specifically including: The tilt angle at time t As a tilted particle, and the size is The tilt angle particle swarm is initialized, and the position is set to and speed is set to ; in, is the preset minimum tilt angle of the photovoltaic panel, is the preset maximum tilt angle of the photovoltaic panel, is a random number; The updated speed of the particle with the i+1th tilt angle ,in, is the velocity inertia weight of the particle at the tilt angle, is the optimal position of the particle itself at the tilt angle, is the global optimal position of the particle swarm with tilt angle, is a random number, and is the learning factor, which is used to approach the particle’s own optimal position and the global optimal position; The updated position of the particle with the i+1th tilt angle = + ,in Update the scaling factor for the tilt angle particles to adjust the velocity's influence range and unify the units; set the optimization objective function F( )=max( - ), continuous iteration During the iteration, the velocity inertia weight of the tilted particle is dynamically adjusted with the number of iterations, and the output is optimized to achieve the objective function F( ) Maximum optimal tilt angle ; The tilt angle adjustment module is used to adjust the servo motor control parameters of the photovoltaic panel to control the tilt angle and adjust the tilt angle to the optimal tilt angle. .

9. A photovoltaic panel output control device, characterized in that: The photovoltaic panel output control device includes: a memory, a processor, and a photovoltaic panel output control program stored in the memory and executable on the processor. When the photovoltaic panel output control program is executed by the processor, the photovoltaic panel output control method described in any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product comprises a photovoltaic panel output control program, and when the photovoltaic panel output control program is executed by a processor, the photovoltaic panel output control method described in any one of claims 1 to 7 is implemented.

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