Automation of field inspection in large scale solar farms

Automation of field inspection in large scale solar farms

, Credit: Equinor, APODI, ,

Credit: Equinor

The goal is to realize efficient and automated system for solar module
inspection and optimize energy production (i.e. high yield and warranty
claims) in large scale solar installations. Solar is the fastest growing segment
in the energy industry, because of the simple installation and short time to
production. Solar farms now contain more than 1 million individual modules,
requiring larger space and continuous maintenance for keeping high
productivity. Having recently changed its name, Equinor (formerly Statoil) has
a mission to invest in renewable energy and to develop its business within
green energy. Through joint ventures with Scatech Solar, Equinor intends
to use the global presence to expand the portfolio to become a diversified
energy company where solar will be part of Equinor new businesses to put
the company at the front of green energy industries. An efficient, automated
and autonomous inspection and analysis system will be an important tool for
both monitoring their investment and optimizing the yield.
Manual inspection of solar systems in the field is common today.
Interpretation of the IR thermal images is complicated by artefacts that
appear in data and dirt on modules, which may not be easily distinguishable
from faults. Also, correlation between visual and electrical data is often not
practical. With the large installations of today, manual inspection is no longer
efficient. Therefore, sophisticated approaches are necessary to determine
when defects have a sufficient impact on the energy production to warrant
replacement of solar modules. This project aims to realize fault models from the field arrays, high-resolution and multispectral sensing for automated airborne monitoring and inspection from remote distances. Machine learning will be established to correlate inspection with electrical data to evaluate the impact of the defects on the production. A cost-benefit analysis will be integrated to control the operation and maintenance of solar farms.

Project facts


Automation of field inspection in large scale solar farms




01.02.19 - 31.01.22

Total budget

20.400.000 NOK

Research group



Research Council of Norway (RCN)

Project members

Ingunn Burud
Thomas Odijk Håvardstun
Agnar Sivertsen
Fabio Andrade
Nadia Noori