Cleaning optimization reduces risk
and improves revenues in desert regions​

Product / Cleaning Optimization

Especially in very dry regions, soiling losses can be a major issue, leading to significant loss of production and thus of revenue. When selecting the right cleaning system, it is all about weighing the cost against the benefits. Autonomous cleaning robots allow a very high cleaning frequency but require an initial investment. Tractor and brush solutions are more flexible but result in higher soiling losses. Frequent or even sporadic rain can have a positive impact, reducing the necessity to clean.

PVRADAR simulates the effect of intelligent cleaning solutions for a specific project and business model.

To find the most cost-efficient cleaning strategy many different scenarios must be calculated and compared. For a fair comparison, our optimization model first optimizes parameters for each solution individually, then selects overall best solution: fully-autonomous and semi-autonomous cleaning robots, tractor plus brush as well as manual cleaning.

PVRADAR calculates the optimal cleaning dates for each cleaning technology individually. By integrating critical information such as soiling rate and rain from satellite data, we ensure accurate results and improve our user's experience.

Our financial model translates energy gains into revenue increases and compares them against the additional investment and operational costs of the cleaning system. Within minutes our users find the cleaning strategy that best fits the powerplant and its conditions and that maximizes the financial result of the project.