  Enabling deep penetration of distributed energy resources (DERs) requires
comprehensive monitoring and control of the distribution network. Increasing
observability beyond the substation and extending it to the edge of the grid is
required to achieve this goal. The growing availability of data from
measurements from inverters, smart meters, EV chargers, smart thermostats and
other devices provides an opportunity to address this problem. Integration of
these new data poses many challenges since not all devices are connected to the
traditional supervisory control and data acquisition (SCADA) networks and can
be novel types of information, collected at various sampling rates and with
potentially missing values. Visualization and analytics for distributed energy
resources (VADER) system and workflow is introduced as an approach and platform
to fuse these different streams of data from utilities and third parties to
enable comprehensive situational awareness, including scenario analysis and
system state estimation. The system leverages modern large scale computing
platforms, machine learning and data analytics and can be used alongside
traditional advanced distribution management system (ADMS) systems to provide
improved insights for distribution system management in the presence of DERs.
