Photovoltaic panel inclination angle dynamic detection and adaptive adjustment system

Abstract

The invention discloses a photovoltaic panel inclination angle dynamic detection and adaptive adjustment system, and relates to the technical field of photovoltaic equipment. The system comprises a photovoltaic panel, a multi-sensor fusion detection module, an integrated intelligent maintenance mechanism, a mechanical adjustment mechanism, a controller, a meteorological data linkage module, a wireless communication and cloud monitoring module and a solar auxiliary power supply module, the multi-sensor fusion detection module is composed of an illumination intensity sensor, an image recognition sensor and a tilt angle sensor, the integrated intelligent maintenance mechanism comprises an automatic cleaning assembly and a mechanical overload protection mechanism, and the controller overall plans all the modules to achieve dynamic detection and self-adaptive adjustment of the tilt angle of the photovoltaic panel. According to the invention, the problems of easy shielding interference, low maintenance automation degree and the like of traditional system detection are solved, automatic maintenance and overload protection of the photovoltaic panel are realized, environmental adaptability is enhanced in combination with meteorological data, remote operation and maintenance can be realized, and photovoltaic power generation efficiency is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic equipment technology, and in particular to a dynamic detection and adaptive adjustment system for the tilt angle of a photovoltaic panel. Background Technology

[0002] In photovoltaic (PV) power generation systems, the tilt angle of PV panels directly affects the light reception efficiency, which in turn determines the power generation. Therefore, accurate detection and reasonable adjustment of the tilt angle are crucial for improving the efficiency of PV power plants. Current technologies often employ a single light sensor or tilt sensor for PV panel tilt angle detection. This presents the problem of data susceptibility to external interference: for example, if the surface of the light sensor is obstructed by dust, snow, bird droppings, etc., it will directly lead to distorted light data, resulting in incorrect tilt angle adjustment decisions. Furthermore, relying solely on a tilt sensor cannot achieve dynamic adjustment based on real-time changes in light intensity; adjustments can only be made according to fixed time periods or preset angles, lacking flexibility.

[0003] To address the aforementioned issues in photovoltaic panel maintenance, current cleaning methods primarily rely on regular manual wiping. This not only results in high maintenance costs but also lacks targeted timing. When sensor areas are partially obstructed, timely cleaning is impossible, leading to long-term data distortion. Furthermore, the mechanical mechanisms for adjusting photovoltaic panel tilt angles generally lack effective overload protection. In situations such as strong winds or mechanical jamming, the motors are prone to overload and burnout, causing equipment damage and power generation interruptions.

[0004] In addition, most existing photovoltaic panel tilt adjustment systems are not linked to meteorological data, making it impossible to take protective measures in advance based on future wind speed, rain, snow and other weather conditions. In windy weather, photovoltaic panels that are kept at a large tilt angle are easily damaged by strong winds. After rain or snow, the dust on the surface of photovoltaic panels cannot be effectively washed away by natural precipitation.

[0005] In summary, existing photovoltaic panel tilt angle detection and adjustment technologies have significant shortcomings in terms of detection accuracy, maintenance automation, and environmental adaptability, which restricts the further improvement of photovoltaic power generation efficiency. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, the present invention provides a dynamic detection and adaptive adjustment system for the tilt angle of photovoltaic panels, which aims to solve the problems of traditional systems being easily affected by shading interference, having a low degree of automation in maintenance, and lacking weather forecasting and intelligent optimization capabilities for tilt angle adjustment.

[0007] The technical solution adopted in this invention is as follows:

[0008] This invention provides a dynamic detection and adaptive adjustment system for the tilt angle of a photovoltaic panel. The system includes a photovoltaic panel, a multi-sensor fusion detection module, an integrated intelligent maintenance mechanism, a mechanical adjustment mechanism, and a controller. The controller is electrically connected to the multi-sensor fusion detection module, the integrated intelligent maintenance mechanism, and the mechanical adjustment mechanism. The system also includes a meteorological data linkage module, a wireless communication and cloud monitoring module, and a solar auxiliary power supply module for powering various power-consuming devices, all communicatively connected to the controller. The multi-sensor fusion detection module includes a light intensity sensor for collecting light data, an image recognition sensor for detecting shading status, and a tilt angle sensor for collecting tilt angle data. The integrated intelligent maintenance mechanism includes an automatic cleaning component and a mechanical overload protection mechanism. The mechanical adjustment mechanism is connected to the rotation axis of the photovoltaic panel and is driven by the controller to adjust the tilt angle of the photovoltaic panel.

[0009] Preferably, the light intensity sensor is a silicon-based photodiode sensor, which is deployed in the unobstructed central area of ​​the photovoltaic panel surface, and two such sensors are configured on the photovoltaic panel to form redundant detection.

[0010] Preferably, the image recognition sensor is a miniature industrial camera, installed on the side of the photovoltaic panel bracket, with the lens facing the light intensity sensor area.

[0011] Preferably, the tilt sensor is a MEMS-type dual-axis tilt sensor, integrated at the rotation axis of the photovoltaic panel, and coaxially mounted with the rotation axis of the photovoltaic panel, with a measurement range of ±90°.

[0012] Preferably, the automatic cleaning component includes a miniature stepper motor, a nylon brush, and a guide rail slide. The nylon brush is mounted on the slider of the guide rail slide, and the cleaning stroke covers the light intensity sensor and the easily dust-accumulating areas on the edges of the photovoltaic panel.

[0013] Preferably, the mechanical overload protection mechanism includes a strain gauge torque sensor, which is mounted on the output shaft of the stepper motor, and the overload threshold is set to 120% of the rated torque of the motor.

[0014] Preferably, the meteorological data linkage module connects to a third-party meteorological platform via an RS485 / Ethernet interface to obtain four core data types for the next 24 hours: sunshine forecast, wind speed, rainfall, and snowfall. The data is updated every hour, and the connected meteorological data is checked for errors. If the deviation exceeds 30%, the local sensor data shall prevail.

[0015] This invention provides a method for dynamic detection and adaptive adjustment of the tilt angle of a photovoltaic panel, comprising the following:

[0016] Step 1: Multi-sensor data acquisition. The controller drives the multi-sensor fusion detection module, which collects light intensity data on the surface of the photovoltaic panel by the light intensity sensor, obtains real-time tilt angle data of the photovoltaic panel by the tilt angle sensor, and simultaneously captures image information of the sensor area by the image recognition sensor.

[0017] Step 2: Intelligent recognition of shading status. The controller processes the images collected by the image recognition sensor and determines whether there is shading in the photovoltaic panel sensor area and the percentage of shading area based on pixel features.

[0018] Step 3: Data fusion and compensation. Based on the occlusion determination results, the controller performs weighted fusion calculations on the illumination and tilt angle data. When occlusion occurs, historical related data is called to generate temporary illumination reference values.

[0019] Step 4: Meteorological data access verification. The meteorological data linkage module acquires meteorological data for the next 24 hours, and the controller performs error verification on it. If the deviation exceeds the threshold, the local sensor data shall prevail.

[0020] Step 5: Cleaning task decision and execution. Based on the obstruction situation, the controller drives the automatic cleaning components of the integrated intelligent maintenance mechanism to carry out cleaning operations in the sensor area.

[0021] Step 6: Optimal tilt angle calculation and planning. The controller combines the fused data with the verified meteorological data to analyze the optimal tilt angle and adjustment scheme for the photovoltaic panels.

[0022] Step 7: Tilting angle mechanical adjustment is implemented. The controller sends an adjustment command to the mechanical adjustment mechanism, which drives the photovoltaic panel to rotate and complete the precise adjustment of the tilt angle.

[0023] Section 8: Mechanical overload protection response. The integrated intelligent maintenance mechanism monitors the motor torque in real time. When an overload occurs, the controller immediately triggers power-off and reverse unloading operations.

[0024] Step 9: Data Cloud Interaction and Feedback. The wireless communication and cloud monitoring module uploads the status and adjustment data of the photovoltaic panels to the cloud, and at the same time receives remote control commands issued by the cloud.

[0025] Compared with existing technologies, the beneficial effects of this invention are:

[0026] 1. In this invention, the multi-sensor fusion detection module effectively solves the limitations of single-sensor detection. Through image recognition occlusion detection and data compensation mechanisms, it improves the detection accuracy of illumination and tilt angle data and avoids adjustment errors caused by occlusion.

[0027] 2. In this invention, the integrated intelligent maintenance mechanism realizes automated cleaning of the photovoltaic panel sensor area, reducing the frequency of manual cleaning. At the same time, the mechanical overload protection mechanism reduces the equipment failure rate and significantly extends the service life of the mechanical adjustment mechanism.

[0028] 3. In this invention, the proactive protection strategy of the meteorological data linkage module can effectively reduce the damage to photovoltaic panels caused by severe weather such as strong winds, rain and snow. Furthermore, the wireless communication and cloud monitoring module enables remote operation and maintenance of the photovoltaic power station, allowing managers to monitor equipment status and power generation data in real time, thereby improving operation and maintenance efficiency. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the overall structure of the photovoltaic device in this invention.

[0030] Figure 2 for Figure 1 Enlarged structural diagram of part A in the middle

[0031] Figure 3 This is a schematic diagram of the logic flow of the system control method of the present invention.

[0032] Figure labeling: 1-Photovoltaic panel, 2-Light intensity sensor, 3-CMOS image recognition sensor, 4-Tilt sensor, 5-Automatic cleaning component, 6-Mechanical adjustment mechanism, 7-Controller, 8-Meteorological data linkage module, 9-Wireless communication and cloud monitoring module, 10-Solar auxiliary power supply module, 11-Mechanical overload protection mechanism, 51-Miniature stepper motor, 52-Nylon brush, 53-Guide rail slide, 1101-Strain gauge torque sensor. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0034] Example 1

[0035] The photovoltaic panel tilt angle dynamic detection and adaptive adjustment system of the present invention includes a photovoltaic panel 1, a multi-sensor fusion detection module, an integrated intelligent maintenance mechanism, a mechanical adjustment mechanism 6, and a controller 7.

[0036] The controller 7 is electrically connected to the multi-sensor fusion detection module, the integrated intelligent maintenance mechanism, and the mechanical adjustment mechanism 6. The controller 7 is also connected to the meteorological data linkage module 8, the wireless communication and cloud monitoring module 9, and the solar auxiliary power module 10.

[0037] The multi-sensor fusion detection module includes a light intensity sensor 2, a CMOS image recognition sensor 3, and a tilt sensor 4. The light intensity sensor 2 is a silicon-based photodiode sensor, deployed in the unobstructed central area of ​​the photovoltaic panel 1 surface. Each photovoltaic panel 1 is equipped with two light intensity sensors 2 to form redundant detection. The CMOS image recognition sensor 3 is a high-pixel miniature industrial camera that supports a low-power sleep mode. It is installed on the side of the photovoltaic panel 1 support, with the lens facing the area of ​​the light intensity sensor 2. The tilt sensor 4 is a MEMS-type dual-axis tilt sensor with a measurement range of ±90°, integrated at the rotation axis of the photovoltaic panel 1 and coaxially mounted with the rotation axis.

[0038] The integrated intelligent maintenance mechanism includes an automatic cleaning component 5 and a mechanical overload protection mechanism 11. The automatic cleaning component 5 consists of a micro stepper motor 51, a nylon brush 52, and a guide rail slide 53. The micro stepper motor 51 and the nylon brush 52 are mounted on the slider of the guide rail slide 53, and the cleaning stroke covers the light intensity sensor 2 and the area on the edge of the photovoltaic panel 1 where dust easily accumulates.

[0039] The mechanical overload protection mechanism 11 includes a strain gauge torque sensor 1101, which is mounted on the output shaft of the micro stepper motor 51 and has an overload threshold set to 120% of the motor's rated torque.

[0040] The mechanical adjustment mechanism 6 adopts a worm gear reduction mechanism and is connected to the rotating shaft of the photovoltaic panel 1. Under the drive of the controller 7, it realizes precise micro-adjustment of the tilt angle of the photovoltaic panel 1. The rotating shaft is made of stainless steel and equipped with self-lubricating bearings to reduce mechanical wear.

[0041] The meteorological data linkage module 8 connects to a third-party meteorological platform via an RS485 / Ethernet interface to obtain four core data types for the next 24 hours: sunshine forecast, wind speed, rainfall, and snowfall. The data is updated every hour. At the same time, error verification is performed on the accessed data. When the deviation between the forecast data and the real-time data collected by the local sensor is greater than 30%, the local data shall prevail.

[0042] The wireless communication and cloud monitoring module 9 uses either a LoRa wireless module or a 5G module. The LoRa module has a transmission distance of 3-5km and is suitable for large-scale photovoltaic power plants, while the 5G module is suitable for commercial or residential photovoltaic scenarios. This module uploads data such as the tilt angle, power generation, and sensor status of the photovoltaic panel 1 every 5 minutes. It also supports cloud-based commands such as tilt angle adjustment and cleaning task triggering. The cloud platform can generate statistical reports and enable historical data backtracking.

[0043] The solar auxiliary power module 10 includes a micro photovoltaic panel and a rechargeable lithium battery pack mounted on the photovoltaic panel 1 bracket. The output voltage is 12V. When the lithium battery voltage is ≥11V, it prioritizes powering the CMOS image recognition sensor 3, the automatic cleaning component 5, and related sensors. When the voltage is <11V, it automatically switches to photovoltaic panel 1 or grid-connected power supply for auxiliary power.

[0044] Example 2: The working process of the present invention is as follows:

[0045] 1. Data Acquisition and Occlusion Detection: The multi-sensor fusion detection module uses light intensity sensor 2 and tilt sensor 4 to collect real-time data on light intensity and tilt angle of photovoltaic panel 1, while CMOS image recognition sensor 3 acquires images of the sensor area. The system performs grayscale and binarization processing on the images. When the grayscale value of a pixel in the sensor area is lower than a preset threshold, occlusion is determined, and the Canny operator edge detection algorithm is then used to identify the type and area percentage of the occlusion.

[0046] 2. Data Fusion and Compensation: When there is no obstruction, the system assigns a weight of 0.7 to the illumination data and a weight of 0.3 to the tilt angle data for weighted fusion. If the obstruction area is greater than 20%, distorted illumination data is removed, and illumination-tilt angle correlation data from the same period in the past 7 days is used to generate a temporary illumination reference value. At this time, the weight of the tilt angle data is increased to 0.9, and the weight of the historical illumination data is 0.1. When the obstruction is removed and the grayscale value recovers above the threshold for 5 seconds, the system switches back to multi-sensor fusion detection mode within 3 seconds.

[0047] 3. Automatic Cleaning Execution: By default, the system starts the automatic cleaning component 5 at 3:00 AM every day (light intensity < 10W / ㎡), and the cleaning cycle repeats twice. If the sensor occlusion area is detected to be > 20% for 10 minutes, local cleaning is immediately initiated. After cleaning, the CMOS image recognition sensor 3 checks again. If the occlusion area is still > 5%, cleaning is repeated. If cleaning is ineffective after 3 consecutive attempts, a maintenance warning is sent.

[0048] 4. Tilt Adjustment and Overload Protection: Based on the fused illumination and tilt angle data, controller 7 drives mechanical adjustment mechanism 6 to adjust the tilt angle of photovoltaic panel 1. Strain gauge torque sensor 1101 detects motor torque in real time. If the torque exceeds the overload threshold and lasts for 2 seconds, controller 7 immediately cuts off the motor power supply, controls the motor to rotate 5° in the opposite direction to release the load, and then attempts to adjust again. If there are 3 consecutive overloads, the mechanical mechanism is locked, relevant data is recorded, and a fault alarm is sent.

[0049] 5. Meteorological Data Linkage and Protection: The meteorological data linkage module 8 receives and filters meteorological data. If the forecast wind speed is ≥15m / s, the system will adjust the photovoltaic panel 1 to a horizontal position within 10 minutes. After the wind speed drops below 10m / s, the system will restore the optimal power generation tilt angle. When rain, snow, or dust storms are forecast, the automatic cleaning component 5 will be activated in advance for pre-cleaning, and the tilt angle of the photovoltaic panel 1 will be adjusted to a low angle (e.g., 15°). After the rain or snow ends, the optimal tilt angle will be recalculated based on the recovery of sunlight. The system will also fine-tune the tilt angle of the photovoltaic panel 1 15 minutes in advance based on the sunlight forecast trend.

[0050] 6. Model Optimization and Cloud Interaction: The controller 7 has a built-in lightweight machine learning inference engine. Every 7 days, it performs small-batch training on the random forest regression model using local data. Monthly, it uploads all site data to the cloud for deep training, and the optimized model parameters are then sent back to the local machine to continuously improve the accuracy of tilt adjustment. The wireless communication and cloud monitoring module 9 enables data uploading and remote control, allowing administrators to monitor the equipment status in real time through the cloud platform.

[0051] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A photovoltaic panel inclination angle dynamic detection and adaptive adjustment system, characterized in that: the system comprises a photovoltaic panel (1), a multi-sensor fusion detection module, an integrated intelligent maintenance mechanism, a mechanical adjustment mechanism (6), and a controller (7), wherein the controller (7) is electrically connected with the multi-sensor fusion detection module, the integrated intelligent maintenance mechanism, and the mechanical adjustment mechanism (6); the system further comprises a meteorological data linkage module (8), a wireless communication and cloud monitoring module (9), and a solar auxiliary power module (10) for powering each power consumption device, which are all in communication connection with the controller (7); the multi-sensor fusion detection module comprises an illumination intensity sensor (2) for collecting illumination data, an image recognition sensor (3) for detecting the shading state, and an inclination angle sensor (4) for collecting inclination angle data; the integrated intelligent maintenance mechanism comprises an automatic cleaning assembly (5) and a mechanical overload protection mechanism (11); the mechanical adjustment mechanism (6) is connected with the rotating shaft of the photovoltaic panel (1), and is driven by the controller (7) to realize the inclination angle adjustment of the photovoltaic panel (1).

2. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: the illumination intensity sensor (2) is a silicon-based photodiode sensor, which is arranged in the center area of the photovoltaic panel (1) without shading, and two such sensors are arranged on each photovoltaic panel (1) to form a redundant detection.

3. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: the image recognition sensor (3) is a miniature industrial camera, which is installed on the side of the photovoltaic panel (1) support and has a lens facing the area of the illumination intensity sensor (2).

4. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: the inclination angle sensor (4) is a MEMS type dual-axis inclination angle sensor, which is integrated at the rotating shaft of the photovoltaic panel (1) and is coaxially installed with the rotating shaft center of the photovoltaic panel (1), and the measurement range is ±90°.

5. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: the automatic cleaning assembly (5) comprises a miniature stepping motor (51), a nylon brush (52), and a guide rail sliding table (53), wherein the nylon brush (52) is installed on the sliding block of the guide rail sliding table (53), and the cleaning stroke covers the illumination intensity sensor (2) and the dust-prone area of the edge of the photovoltaic panel (1).

6. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: the mechanical overload protection mechanism (11) comprises a strain type torque sensor (1101), which is installed at the output shaft end of the stepping motor, and the set overload threshold is 120% of the rated torque of the motor.

7. The photovoltaic panel inclination angle dynamic detection and adaptive adjustment system according to claim 1, characterized in that: ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ The weather data linkage module (8) accesses a third-party weather platform through an RS485 / Ethernet interface, obtains four types of core data of light prediction, wind speed, rainfall, and snowfall in the next 24 hours, the data update frequency is 1 hour / time, and error checking is performed on the accessed weather data, and when the deviation is more than 30%, the local sensor data is used as the reference.

8. A photovoltaic panel inclination angle dynamic detection and adaptive adjustment method, characterized in that, The photovoltaic panel inclination angle dynamic detection and self-adaptive adjustment system of any one of claims 1 to 7 comprises the following contents: Linkage one, the controller (7) drives the multi-sensor fusion detection module, the light intensity sensor (2) collects the light data on the surface of the photovoltaic panel (1), the inclination sensor (4) obtains the real-time inclination angle data of the photovoltaic panel (1), and the image recognition sensor (3) synchronously captures the image information of the sensor area; Linkage two, the controller (7) processes the image collected by the image recognition sensor (3), and determines whether there is an obstruction in the sensor area of the photovoltaic panel (1) and the area ratio of the obstruction according to the pixel characteristics; Linkage three, the controller (7) calculates the light and inclination angle data according to the obstruction determination result, and calls the historical associated data to generate a temporary light reference value when there is an obstruction; Linkage four, the weather data linkage module (8) obtains the weather data in the next 24 hours, and the controller (7) performs error checking thereon, and when the deviation is more than the threshold, the local sensor data is used as the reference; Linkage five, the controller (7) drives the automatic cleaning component (5) of the integrated intelligent maintenance mechanism to carry out cleaning operation in the sensor area according to the obstruction condition; Linkage six, the controller (7) analyzes the best inclination angle and adjustment scheme of the photovoltaic panel (1) in combination with the fused data and the checked weather data; Linkage seven, the controller (7) issues an adjustment instruction to the mechanical adjustment mechanism (6) to drive the photovoltaic panel (1) rotating shaft to complete the accurate adjustment of the inclination angle; Linkage eight, the mechanical overload protection mechanism (11) of the integrated intelligent maintenance mechanism monitors the motor torque in real time, and the controller (7) immediately triggers the power-off and reverse unloading operation when the overload occurs; Linkage nine, the wireless communication and cloud monitoring module (9) uploads the state and adjustment data of the photovoltaic panel (1) to the cloud, and receives the remote control instruction issued by the cloud.

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