Canadian tech firm Clir Renewables has developed software which uses layered machine learning to identify underperforming wind turbines and the causes . The data also provides duration and lost energy associated with the underperformance. 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 data on the duration of the underperformance , as well as associated lost energy . Additionally , the application identifies 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 data on the duration of the underperformance , as well as associated lost energy . Additionally , the application identifies hardware or software changes which could have prompted the slowdown .