Use Case:
With hundreds of thousands of devices working in tandem at a power plant, there’s a ton of data generated every moment of the plant’s existence. Managing clean energy asset performance is a difficult task that requires knowledge of how energy works electrically, data cleaning and structuring, big data analytics, and machine learning. FutrOS algorithms filter the signals from the large amount of (often noisy) data generated to make it easier to understand how the asset is performing today and how it’d perform in the future.
Impact expected:
Identify lapses in generation (sometimes even before it happens) and correct the anomalies to increase generation
Key Users:
Operations and Maintenance Managers, Site Managers, Asset Managers
Applicable to:
All clean energy assets including but not limited to Solar (rooftop, utility), Wind, and BMS.
