“As a result of continuous innovation by the Kaiserwetter team, we are beyond pleased to offer ARISTOTELES users a broader scope of data intelligence for their renewable energy investments,” said Hanno Schoklitsch, CEO of Kaiserwetter. “With this upgrade, Kaiserwetter makes its debut in the solar power sector which, like wind power, represents an industry that is critical to fulfilling our core mission of accelerating the decarbonization of our global energy system.”

Kaiserwetter’s flagship IoT & AI platform leverages smart data analytics, predictive analytics and machine learning algorithms to maximize the power generation of connected renewable energy installations. With the actionable data intelligence ARISTOTELES offers, financing banks, investors and asset owners can evaluate their respective portfolio’s operational and financial status to help enable early asset failure detection, inform investment decisions and secure their debt service coverage ratio.

“Our next generation of ARISTOTELES is capable of delivering the same caliber of data intelligence for solar power systems. Equally exciting is the addition of global electric power markets analytics, which users can use to calculate and predict in real-time the revenues generated by their connected assets,” said Schoklitsch. “This yields insights into the tradability beyond regulatory feed-in tariffs and helps to compare the long-term attractiveness of different markets since our platform accounts for historical electric power market activity, too.”

The launch of this expanded version of ARISTOTELES coincides with the rapid technical improvement of solar power equipment, including PV modules, which has made solar energy significantly more cost-effective, productive and competitive with wind and other energy sources than it was just one decade ago. Investors have taken note and have progressively ratcheted-up their engagement in the solar power sector.

Kaiserwetter upgraded ARISTOTELES to facilitate and accelerate this trend. Today, ARISTOTELES is capable of integrating data from solar power installations ranging in size from 10-kW rooftop systems to over 200-MW utility-scale solar parks and using machine learning algorithms to forecast power output, anticipate the effects of context factors and benchmark the financial performance of a user’s assets against that of their peers.

By integrating electricity market data, ARISTOTELES enables the comparison of a user’s own revenues with global electric power market price curves, making analysis of potential asset revenue more precise than ever. In combination with external data, such as meteorological factors, ARISTOTELES enables investors and renewable energy asset owners to both continuously maximize the operational and financial performance of their wind and solar investments and minimize investment risks.