Canadian tech firm Clir Renewables has developed software which uses layered machine learning to identify underperforming wind turbines and the causes. The application works alongside algorithms in the software to analyse and classify data. Clir’s technology is based on a combination of data from weather stations around the world as well as satellite images taken by satellites that can be used for analysis. Additionally, the application spotlights hardware or software changes which could have prompted the slowdown.
Canadian tech firm Clir Renewables has developed software which uses layered machine learning to identify underperforming wind turbines and the causes. The application works alongside algorithms in the software to analyse and classify data. It can also create a “synthetic event” when power output drops significantly and gather information on the duration of the underperformance, as well as associated lost energy. Additionally, the application spotlights hardware or software changes which could have prompted the slowdown.