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Thermal Abnormalities

Thermal Anomalies, the most common problems of solar power plant equipment, are related to PV modules and inverters. PV module defects can be up to 20% below module performance. It is very important to detect these problems as soon as possible.

If you want to make sure that your photovoltaic system is operating at maximum capacity, you need to conduct a thorough inspection.

Inspection with drones, analysis of data and a detailed report with a locator map of these anomalies makes the maintenance process much more efficient. It saves time and allows monitoring the operation of the photovoltaic system throughout its lifetime.

Identifying possible damage in a photovoltaic plant can prevent major losses in energy production, economic losses and possible fires.

The most common abnormalities are;

“HOT SPOT” or “CELL”

It is the most common type of damage that occurs when a cell in the panel overheats. This can be seen in the thermal image as a point where the temperature is higher than the rest of the panel. When in RGB view, in some cases we can identify what is causing this overheating.

Abnormality Classes

For allocation into classes of abnormality (CoA), specific patterns and measured temperature must be compared with thermographic image samples and temperature differences. It is not always possible to classify thermal anomalies beyond doubt using thermography inspection alone. In this case additional appropriate inspections will be applied.

Anomalies of PV Modules

Thermal images and the resulting temperature differences must always be evaluated in the context of ambient conditions, mounting type and module assembly (glass-glass module, glass-foil module, integrated polymers, etc.).

If a classification is not possible without doubt from the front side of a PV module, a back side view or further measurement techniques should be used.

Abnormalities of Other CSF Components

BOS component inspection includes but is not limited to cables, contacts, fuses, switches, inverters and batteries. The classification of anomalies will depend on the BOS component.

Inspection Report

  • The PV inspection report shall contain the following information;
  • Name of the PV expert, thermographer and persons involved
  • Type of camera system, including brands and models
  • Examination day and time
  • Place of examination

Scope of inspection according to the contract;

  • By type designation of components
  • Efficiency of PV modules, nominal value of BOS components
  • List of all inspected components
  • Assembly

Environmental Conditions;

  1. Wind speed, Bft or m/s and direction,
  2. Cloud coverage, octa and cloud type,
  3. Radiation in the modulus plane in W/m2,
  • Contamination of the component with photos as evidence (mainly important for PV modules)
  • Description of the inspection procedure
  • List of thermal discernible points identified with a description of their location within the PV plant, using at least 2 of the possible descriptions for each item;

PV Modules:

  • Serial number
  • A photo showing the position of the module in the array
  • XY coordinates, clear definition of column and row
  • Marking in system documents (sequence or table/roof plan)
  • Permanent marking of the module in place

Other BOS: Serial number

  • Mark the place on the IR photo indicating the location of the opening in the photo
  • Permanent marking of the component in place
  • Proposed actions based on the classification of anomalies
  • Summary of results

For thermal anomalies within a module, the thermographic image should show at least one whole module, showing the position of the junction box and the bottom edge within the installation. Additional thermographic images of detailed views can be attached for further clarification.

The following steps will be included for each thermographic image;

  • Full description of the object
  • File name, date and time the thermographic image was taken
  • Camera system with serial number and lens
  • Emission used and temperature recorded
  • Full description of the location in solar power plants enabling the customer to clearly identify the anomaly
  • Providing a photograph of sufficient resolution to visually distinguish details in the thermographic image when urgent action is required
  • Detailed examinations, temperatures or temperature difference in thermal abnormality
  • Conclusions and recommendations for subsequent checks

Modules with higher efficiency will reach a lower normal operating absolute temperature.

We used machine learning to analyze the data obtained from airborne thermal inspections in SPP systems. Artificial intelligence technology developed with image processing and deep learning techniques obtains the heat distribution data of PV panels with air thermography of photovoltaic systems and detects hot spots on the panels. According to these temperature distributions, it determines the type of failure and thus minimizes the possibility of making mistakes in fault detection.

MapperX analyzes data by minimizing the margin of error with artificial intelligence decision-making algorithms. We shape the future with our MapperX autonomous artificial intelligence software, which we designed and developed with 100% domestic facilities. You can review our Thermal Abnormalities article.