AI lends support for issues relating to solar energy including solar forecasting, asset maintenance, and soiling of panels.

The ramifications from climate change are becoming clearer everyday as mankind confronts extreme weather instances across the globe. Renewable energy, particularly solar, has become of paramount importance in the race to achieve 2050 climate targets and replace fossil sources as early as possible. AI is being increasingly deployed to accelerate and optimize the use of solar power by solving a range of problems. (PV Magazine USA)

Solar energy forecasting

Solcast, an Australian solar forecasting vendor that offers a model featuring an Artificial Neural Network (ANN)—a complex, trained and multi-layered AI computing system – provides more than 600 million calculated forecasts per hour to its solar customers.

Large-scale solar sites use Solcast’s predictions for weather and sky characteristics through geo-codes, quality controls, solar irradiance estimates, real-time solar farm power data feeds and ground-based sky images of local cloud coverage.

The AI-based forecasts are 10 to 15% more accurate compared to previous estimates from the Australian Energy Market Operator (AEMO).

Asset Maintenance

Maintenance of solar panels can now be carried out faster and more accurately through the use of AI-enabled drones that capture images of the panels. This aerial imagery can be analyzed by an AI algorithm to spot the panels needing maintenance as well as the overall condition of the solar farm.

This is a vast improvement over the earlier, manual, error-prone method that needed a number of workers to manually inspect the panels.

Soiling mitigation

Dust, bird droppings, pollen and other particles accumulate and harden on PV panel arrays, leading to “soiling.”

Soiling blocks sunlight and can also damage the panel components. Solar farm operators would, therefore, turn to soiling stations to address this issue using a comparative energy-loss measurement method.

However, they now have an alternative – AI platforms can analyze the data flowing from the solar panels to assess when and how panels should be cleaned, thus helping increase efficiency and reduce costs.

Related Story:  Terabase Energy Raises $44M For Automating The Construction Of Utility Scale Solar

Image by StockSnap from Pixabay