AI-ENABLED SYSTEM FOR REAL-TIME MONITORING AND OPTIMIZATION OF SOLAR PANEL PERFORMANCE

Abstract

The present invention relates to a system (100) for monitoring and optimizing the performance of solar panels. The system comprises a data acquisition module (1) for collecting real-time data on environmental and operational parameters such as temperature, light intensity, and energy output. Integrated with the data acquisition module (1), a diagnostic module (2) uses an artificial intelligence (AI) algorithm to analyze performance data, detect deviations, and predict faults in the solar panel system. An energy optimization unit (3) communicates with the diagnostic module (2) to adjust operational settings, including panel tilt angle and initiate an automatic cleaning mechanism to remove dust and debris. This automatic cleaning mechanism is activated based on detected dust accumulation or environmental factors that impact energy efficiency, ensuring optimal energy capture. The system further includes a remote monitoring and control interface (4) accessible via a mobile application, allowing authorized users to view performance metrics, historical data, and real-time diagnostics, and make adjustments remotely. Additional modules include a maintenance scheduling module for proactive alerts, an energy storage monitoring module for tracking associated batteries, and a reporting module for generating detailed reports on system efficiency and health. The system’s self-sustained power source enables independent operation, providing a robust solution for maximizing solar energy output and extending panel life.

Specification

Description:FIELD OF INVENTION
The present invention relates to systems and methods for monitoring and optimizing the performance of solar panels. Specifically, it provides a comprehensive solution integrating real-time data acquisition, diagnostic analysis, energy optimization, and remote monitoring functionalities.
More particularly, the present invention is related to AI-enabled system for real-time monitoring and optimization of solar panel performance.
BACKGROUND & PRIOR ART
The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in-and-of-themselves may also be inventions.
With the increasing adoption of solar power as a sustainable energy source, ensuring optimal performance and longevity of solar panels is crucial. Currently, performance monitoring systems for solar panels are limited in diagnostic and predictive capabilities, which can lead to inefficiencies and potential damage if faults go unnoticed. Further, the lack of remote monitoring and control in many existing systems results in limited responsiveness to environmental changes and unforeseen issues. The present invention addresses these limitations by offering a system that continuously monitors, diagnoses, and optimizes solar panel performance to improve energy output and operational lifespan.
The rapid growth in renewable energy, particularly solar energy, has driven substantial investments in solar panel installations worldwide. Solar power, being a clean and sustainable energy source, is a critical component in reducing dependency on fossil fuels and minimizing environmental impacts. However, maximizing the efficiency and longevity of solar panels remains a challenge, as panel performance can be affected by various factors, including environmental conditions, physical degradation, and technical issues within the solar energy system. Conventional systems often lack advanced diagnostic capabilities, resulting in decreased energy output and costly maintenance needs over time.
Most traditional solar monitoring systems provide limited information on basic parameters like energy output and surface temperature. These systems are typically unable to diagnose faults, predict performance degradation, or recommend corrective actions, leading to potential energy losses and expensive reactive maintenance. Additionally, many current monitoring solutions require physical presence at the installation site for adjustments and maintenance, which can be inconvenient and inefficient, especially for installations in remote or large-scale solar farms.
Solar panel efficiency is impacted by several factors, including dust accumulation, shading, soiling, adverse weather conditions, and changes in sunlight angle. Without the ability to detect and respond to these variables, the efficiency and durability of solar installations can be significantly compromised. Predictive maintenance, such as detecting minor performance deviations before they escalate into major faults, can save on repair costs and prevent potential downtimes. However, existing systems often lack the integration of advanced technologies like artificial intelligence (AI) for fault prediction, which limits their effectiveness in supporting proactive and preventative maintenance.
In addition, the emerging need for remote monitoring and control capabilities in solar panel systems has not been fully addressed by current solutions. With the advent of mobile technologies, users expect real-time data accessibility and the ability to remotely optimize and control their systems to match changing environmental conditions. Conventional systems often require third-party devices or software to provide even basic remote access, resulting in fragmented solutions that do not fully integrate with the solar panel's operational system.
The present invention addresses these limitations by providing a fully integrated system for solar panel performance monitoring, diagnostics, optimization, and remote control. This system combines real-time data acquisition, advanced diagnostic algorithms, and AI-driven optimization with a user-friendly interface that allows remote access via a mobile application. Additionally, the invention includes modules for energy storage monitoring, maintenance scheduling, and performance reporting, making it a comprehensive solution for enhancing solar energy output and extending the operational lifespan of solar installations. This invention is particularly advantageous for users seeking a scalable, efficient, and autonomous solution for managing solar energy systems, from small residential setups to large solar farms.
As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.
The use of any and all examples, or exemplary language (e.g. "Such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
The above information disclosed in this Background section is only for the enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.
OBJECTIVE OF THE INVENTION

The main objective of this invention is to provide a system that efficiently monitors and optimizes solar panel performance, leveraging real-time data and diagnostic analysis to adjust operational parameters, detect faults, and allow remote control and maintenance scheduling, thereby enhancing energy output and operational efficiency.
SUMMARY
Before the present systems and methods, are described, it is to be understood that this application is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the present application.
The invention provides a comprehensive system (100) for monitoring and optimizing the performance of solar panels by combining real-time data acquisition, intelligent diagnostics, and energy optimization in a single integrated solution. The system includes a data acquisition module (1) that collects critical operational and environmental data such as temperature, light intensity, and energy output, which are essential for assessing solar panel performance. This data is processed by a diagnostic module (2), equipped with an artificial intelligence (AI) algorithm that detects deviations in performance, identifies faults, and predicts potential failures, ensuring that maintenance needs are addressed proactively.
An energy optimization unit (3) is communicatively linked to the diagnostic module, allowing the system to automatically adjust key operational parameters, such as tilt angle and cleaning schedules, in response to real-time environmental conditions. This adjustment capability enhances energy efficiency and prolongs the solar panels' operational life. To provide users with convenient access and control, the system includes a remote monitoring and control interface (4), accessible via a mobile application, which displays real-time data, historical performance metrics, and diagnostics. The remote interface allows users to make adjustments to panel settings remotely, further maximizing energy efficiency without requiring physical presence at the site.
The system also includes additional features, such as a maintenance scheduling module, which issues alerts for timely maintenance, and an energy storage monitoring module, which tracks the performance of associated storage devices like batteries. A reporting module generates comprehensive reports on system performance, offering insights and recommendations for further optimization. Overall, this invention offers a robust, autonomous, and user-friendly solution that enhances the operational efficiency, durability, and convenience of solar energy systems, making it suitable for a wide range of applications from residential rooftops to large-scale solar farms.
The present invention is directed toward a system for monitoring and optimizing the performance of solar panels. The system comprises:
1. Data Acquisition Module: Captures real-time data on environmental conditions and operational metrics.
2. Diagnostic Module: Analyzes data to detect deviations, faults, and patterns indicative of potential failures.
3. Energy Optimization Unit: Adjusts parameters such as tilt angle and cleaning schedules based on diagnostics to enhance output.
4. Remote Monitoring and Control Interface: Allows remote access to data and adjustments to operational settings.
5. Additional Modules: Maintenance scheduling, energy storage monitoring, and reporting for enhanced diagnostic accuracy and system management.

BRIEF DESCRIPTION OF DRAWINGS

To clarify various aspects of some example embodiments of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It is appreciated that these drawings depict only illustrated embodiments of the invention and are therefore not to be considered limiting in its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure:
Figure 1 shows block diagram representation of AI-enabled system for real-time monitoring and optimization of solar panel performance.

DETAIL DESCRIPTION

The present invention is related to AI-enabled system (100) for real-time monitoring and optimization of solar panel performance.
Figure 1 shows block diagram representation of AI-enabled system for real-time monitoring and optimization of solar panel performance.
The system for monitoring and optimizing the performance of solar panels, referred to as "system (100)," comprises a set of interconnected modules, each designed to provide specific functionalities essential for monitoring and optimizing solar panel performance.
1. Data Acquisition Module (1)
The data acquisition module (1) is configured to capture real-time data from sensors integrated with the solar panels. This module collects data on:
• Temperature: Solar panel temperature and ambient temperature.
• Light Intensity: Sunlight levels impacting energy production.
• Energy Output: The energy generated by the solar panels.
In one embodiment, additional sensors capture data on the tilt angle of the panels, the temperature of photovoltaic cells, and ambient weather conditions, enhancing diagnostic and predictive maintenance functions.

2. Diagnostic Module (2)
The diagnostic module (2) is integrated with the data acquisition module (1) to analyze collected data, detect performance deviations, and identify faults in the solar panel system. This module utilizes an artificial intelligence (AI) algorithm to:
• Identify patterns in performance degradation.
• Predict potential system failures before they occur.
• Detect specific issues such as wiring malfunctions, inverter problems, or cell degradation, suggesting corrective actions.
The AI algorithm continually learns from historical performance data, improving its predictive accuracy over time.
3. Energy Optimization Unit (3)
The energy optimization unit (3) is communicatively linked to the diagnostic module (2) to adjust the operational parameters of the solar panels. Based on the diagnostics, this unit can:
• Automatically adjust the tilt angle and cleaning schedule of the panels based on environmental factors, such as dust accumulation, rainfall, and seasonal sunlight variations.
• Optimize energy output by fine-tuning panel settings to align with real-time environmental conditions.• Activate an automatic cleaning mechanism that initiates cleaning procedures on the solar panel surface to remove dust, dirt, or other obstructions based on real-time data. The cleaning mechanism is triggered based on detected dust accumulation, low energy output due to surface soiling, or environmental data indicating prolonged periods without rainfall that might contribute to surface buildup. This feature helps maintain optimal energy efficiency by ensuring that the panel surface remains clean and capable of capturing maximum sunlight. The automatic cleaning mechanism may use water jets, air blowers, or a robotic cleaning brush, depending on the installation type and environmental conditions.
3. Remote Monitoring and Control Interface (4)

The remote monitoring and control interface (4) provides real-time access to performance data, allowing users to monitor and control system settings remotely. This interface, accessible via a mobile application, enables authorized users to:
• View real-time performance metrics, historical data, and diagnostics.
• Adjust solar panel settings, such as tilt angle and cleaning schedules, remotely to maximize energy efficiency.
5. Additional Modules
Maintenance Scheduling Module: This module generates alerts for necessary maintenance actions based on diagnostic data and provides suggestions for system calibration to enhance performance efficiency.
Energy Storage Monitoring Module: Monitors the charge and discharge rates of associated energy storage devices, such as batteries, and recommends optimal energy storage strategies based on predicted energy production and usage patterns.
Reporting Module: Generates detailed reports on energy production efficiency, diagnostics, and optimization outcomes. These reports include suggestions for improving system performance and can be viewed through the remote monitoring interface.

ADVANTAGES OF THE INVENTION

• Provides comprehensive real-time monitoring and fault detection capabilities for solar panels.
• Optimizes energy output through AI-based diagnostics and parameter adjustments.
• Enables remote access and control, facilitating efficient maintenance and performance management.
• Self-sustained power source from the solar panels, reducing dependency on external power.
Although implementations of the invention have been described in a language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations of the invention.



, C , Claims:1. A system (100) for monitoring and optimizing the performance of solar panels, comprising:
A data acquisition module (1) configured to collect real-time data on temperature, light intensity, and energy output from one or more solar panels;
A diagnostic module (2) integrated with the data acquisition module (1), wherein the diagnostic module (2) detects and analyzes performance deviations and potential faults in the solar panel system;
An energy optimization unit (3) communicatively linked to the diagnostic module (2), wherein the energy optimization unit (3) adjusts operational parameters of the solar panels to enhance energy output based on diagnostic data;
An automatic cleaning mechanism linked to the energy optimization unit (3), configured to initiate cleaning of the solar panel surface based on detected dust accumulation or environmental conditions that impact energy efficiency; and
A remote monitoring and control interface (4), wherein the interface provides access to the real-time performance data and allows remote adjustment of solar panel settings to maximize energy efficiency without physical presence at the installation site.

2. The system (100) of claim 1, wherein the data acquisition module (1) further comprises sensors for capturing data on solar panel tilt angle, photovoltaic cell temperature, and ambient weather conditions, with the data used to enhance system (100) diagnostics and predictive maintenance.

3. The system (100) of claim 1, wherein the diagnostic module (2) includes an artificial intelligence (AI) algorithm that identifies patterns in performance degradation and predicts potential system (100) failures before they occur.


4. The system (100) of claim 1, wherein the energy optimization unit (3) automatically adjusts the tilt angle and controls the automatic cleaning mechanism of the solar panels based on environmental factors such as dust accumulation, rainfall, and seasonal variations in sunlight.

5. The system (100) of claim 1, further comprising a maintenance scheduling module, wherein the module generates alerts for necessary maintenance actions and provides suggestions for system calibration to enhance performance efficiency.


6. The system (100) of claim 1, wherein the remote monitoring and control interface (4) is accessible via a mobile application, allowing authorized users to view performance metrics, historical data, and real-time diagnostics, and make adjustments to solar panel settings from a distance.

7. The system (100) of claim 1, further comprising an energy storage monitoring module, wherein the module tracks the charge and discharge rates of associated energy storage devices such as batteries and recommends optimal energy storage strategies based on predicted energy production and usage patterns.


8. The system (100) of claim 1, wherein the data acquisition module (1) is powered by the energy generated from the solar panels themselves, ensuring that the system (100) operates independently from external power sources.

9. The system (100) of claim 1, further comprising a reporting module configured to generate comprehensive reports detailing energy production efficiency, panel health diagnostics, and system (100) optimization outcomes, with suggestions for improvement.


10. The system (100) of claim 1, wherein the diagnostic module (2) includes fault detection capabilities for identifying issues such as wiring malfunctions, inverter problems, or cell degradation, and suggests corrective actions.

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