VADER is a unified data analytics platform that enables the integration of massive and heterogeneous data streams for granular real-time monitoring with analytics, visualization and control of Distributed Energy Resources (DER) in distribution networks. The project aims to

1. build a set of tools, using data science techniques such as machine learning, to integrate and model a large number of disparate sensor sources to enable distribution system planning and control
2. verify the tools utilizing data from industry and utility partners
3. validate the platform in a pilot testbed combining hardware-in-the-loop simulations and real-time data from hardware deployed in the field.