Machine learning (ML) can be applied at the ‘edge’ where data processing functions are tightly targeted and power consumption must be low.

Nga Nguyen, in UW’s Department of Electrical Engineering and Computer Science, recently received a $503,459 DOE grant for her project titled “Optimal Operation of Large-Scale Energy Storage Systems to ...

To date, there are many algorithms that can estimate the power produced by photovoltaic systems several hours ahead by learning from previous data and analyzing current variables.

When machine learning algorithms are fed a steady stream of real-time data, they can quickly detect bottlenecks, anomalies and other operational inefficiencies.