Photovoltaic Module Energy Loss Estimation via Thermal Imaging
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Solution Overview
Problem
Current methods for detecting and evaluating defects in photovoltaic modules within solar power plants are costly, time-consuming, and lack reliability, often resulting in unnecessary shutdowns and loss of production due to the difficulty in accessing modules and the potential for unjustified repair interventions.
Innovation Solution
A method that estimates energy production loss from defective photovoltaic modules using thermal imaging, dividing the image into temperature zones, determining heat exchange coefficients, and calculating energy loss based on temperature differences, allowing for operational assessment without shutdowns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional maintenance methods (thermal camera inspection and IV tracer testing) are used to detect defective photovoltaic modules, then defect detection capability is improved, but production loss and maintenance cost increase significantly due to required shutdowns and extensive manual inspection
Solution Approach 1:
The system performs preliminary thermal imaging and automated analysis to identify potentially defective modules before any physical inspection or shutdown. By pre-screening modules using thermal cameras and automatically analyzing thermal patterns, the system prepares a targeted list of suspicious modules, allowing maintenance teams to focus only on high-probability candidates rather than inspecting all modules, thus minimizing production loss while maintaining detection reliability
Solution Approach 2:
The invention replaces manual mechanical inspection methods (operators physically examining each module with thermal cameras and IV tracers) with an automated optical-thermal analysis system. The system uses thermal imaging combined with automated image processing algorithms to detect and evaluate defective zones, substituting human labor and time-consuming manual procedures with automated technological systems that operate faster and with consistent accuracy
2Measurement precision
If comprehensive thermal imaging and IV tracer testing are performed on all photovoltaic modules, then measurement precision of defects is improved, but time consumption and operational disruption increase
Solution Approach 1:
Instead of applying uniform inspection procedures to all photovoltaic modules, the system implements local quality assessment by analyzing thermal patterns to identify specific defective zones within modules. The automated analysis focuses computational resources and physical inspection efforts only on modules exhibiting abnormal thermal characteristics, applying different levels of inspection intensity to different locations in the plant based on actual defect probability rather than universal standardized procedures
3Reliability
If repair interventions are triggered based on potential defective areas detected by thermal imaging, then reliability of defect identification is improved, but false positives lead to unjustified production loss
Solution Approach 1:
The system implements feedback mechanisms where thermal imaging results are continuously analyzed and cross-validated. The automated analysis system provides feedback loops that compare thermal patterns against known defect signatures, update detection algorithms based on accumulated data, and adjust inspection criteria dynamically. This feedback system reduces false positives by learning from previous inspections and improving discrimination between actual defects and normal thermal variations
Solution Approach 2:
The invention introduces an automated thermal analysis system as an intermediary between thermal imaging detection and repair intervention decisions. Rather than directly triggering repairs based on raw thermal images, the intermediary analysis system processes thermal data, identifies patterns, evaluates defect probability, and provides reasoned recommendations. This intermediary layer filters out false positives by applying analytical rigor before committing to production-disrupting repair actions
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides a reliable and efficient way to quantify energy production loss from defective modules, reducing unnecessary shutdowns and improving maintenance operations by enabling precise identification of faulty areas without interrupting plant operation.
Implementation Method 1
acquisition of a thermal image of the defective photovoltaic module in operation
Implementation Method 2
division of the thermal image acquired into different temperature zones and determination of the respective temperatures relating to the different zones from the thermal image
Implementation Method 3
determination of the exchange coefficient of the reference photovoltaic module by the following relationship: Upv=G.A−PA⋅T−T∝
Implementation Method 4
calculation of a estimation of the loss of energy production of the module from the temperature difference between the temperature of the hot zone and the reference temperature, of the surface of the hot zone and of a heat exchange coefficient of the module
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
The photovoltaic module (Mi) belongs to a photovoltaic facility. The method comprises the steps of : • acquisition (E1) of a thermal image (Imi) of the defective photovoltaic module (Mi) during operation; • splitting (E2) of the thermal image acquired into various temperatures zones (Zij) and determination of the respective temperatures (Tij) relating to the various zones on the basis of the thermal image (Imi); • obtaining (E5) a reference temperature (Tref) of a reference photovoltaic module; • detection (E6), from among said temperature zones, of at least one hot zone whose temperature is greater than the reference temperature with a temperature deviation of greater than or equal to a predefined minimum value (Tmin); • calculation (E7) of an estimation of the loss of energy production of the module on the basis of the temperature deviation between the temperature of the hot zone and the reference temperature, of the surface area of the hot zone and of a thermal exchange co-efficient of the module.