Swift Navigation, SolarCleano: cleaning robots keep solar power running

A SolarCleano F1A robot tackles a tough cleaning challenge on a solar farm in Saudi Arabia. (Photo: SolarCleano)

SolarCleano, based in Garnich, Luxembourg, makes robots that clean large solar panel installations using GNSS receivers and corrections from Swift Navigation. We asked Christophe Timmermans, SolarCleano’s managing director, a few questions about its technology.

How often do solar panels need to be cleaned?

For decades, it was believed that solar panels did not need to be cleaned due to their angle to the ground and rain. Nowadays, however, the cleaning of solar panels is widely accepted as necessary to optimize a plant’s return on investment (ROI).

How much time per sq. meter do your machines take to clean solar panels?

To provide the fastest possible ROI to our customers, we developed a range of robots to best address the needs of various solar plant layouts. A large utility-scale project with high level of soiling losses in a desert environment will need a very fast and reactive cleaning solution such as our SolarBridge B1, which can clean 24/7/365 fully autonomously. The most suitable solution for a farm rooftop in Germany that needs to be cleaned three to four times a year might be our F1 model, which can clean the equivalent of up to two soccer fields a day. It is designed for rooftops, floating panels and mid-size plants up to 50 MW. While the speed of cleaning is a very important variable, the quality of cleaning is often considered as the driver to performance, which is why we propose different types of brushes depending on the soiling types. Plus, the robot speed can be modified according to the soiling level.

Why do robots need GNSS receivers to clean solar panels?

Moving on inclined, wet glass surfaces makes odometry unreliable because robots might occasionally slip. Therefore, GNSS is the most reliable way to continuously monitor their exact position. Our robots also need path planning because they cannot operate randomly like lawn mowers. Safety is obviously a major concern; we need a very high localization accuracy to ensure that robots don’t fall off the panels. Finally, the largest solar plants are developed in dry, remote locations with high irradiation such as the Sahara, Atacama and Australian deserts. GNSS allows us to have very accurate localization even in those remote areas. In addition, this solution can easily be installed on already-existing solar plants with little capital expenditure.

What spatial accuracy requirements do the robots have for this task?

Safety is our absolute priority. Therefore, our robots need an accuracy of less than 3 cm. They also need to be aware, in real time, of changes in their surroundings, such as maintenance teams, animals and uneven ground.

On large solar farms, GNSS receivers always have a clear line of sight to the satellites and do not suffer from multipath. So, what are the key technical challenges?

Our robots have the additional advantage that they do not need to drive very fast. However, we need to manage fleets of robots on the other side of the world in regions difficult to access and with harsh weather conditions, such as very high or low temperatures and the accumulation of dust behind panels due to air vortices. We need to be able to perform remote maintenance and solve any issue from our control center in Luxembourg. These challenges make our robots increasingly robust. With a current fleet of more than 300 robots around the world, we collect lessons every day to ensure a greater reliability for our upcoming generations of robots.

Why did you choose to partner with Swift Navigation?

We share a vision with Swift: “Accessible automated solutions serving sustainable goals.” We also share other important values, such as “iterate quickly” and “focus on what matters.”