Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meeting: May 18, 2023

Jason Harper, Shibani Ghosh, Mingzhi Zhang, Manoj Kumar Cebol Sundarrajan, Joachim Lohse, Christie-Anne Edie

Research output: NRELPresentation


The U.S. Department of Energy (DOE) Electric Vehicles at Scale Laboratory Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. Critical to this effort is an understanding of the potential grid impacts of EV charging and possible smart charge management (SCM) or vehicle-grid integration (VGI) capabilities that could mitigate these impacts. The EVs@Scale SCM/VGI Pillar is analyzing the impacts of EV charging and developing and demonstrating the capabilities of both SCM and VGI with many different vehicle use cases and grid scenarios. This Deep Dive Discussion from year 2 of the project encompasses the progress and future plans for the analysis components of the FUSE (Flexible charging to Unify the grid and transportation Sectors for Evs at scale) project.
Original languageAmerican English
Number of pages107
StatePublished - 2023

Publication series

NameWebinar presented 18 May 2023

Bibliographical note

Presentations in this webinar include: Smart Charge Management and Vehicle Grid Integration (FUSE); Grid Modeling - Distribution Feeders; EV-Specific Rate Designs and Smart Charging Management; Update: Medium & Heavy Duty Vehicle Charging Analysis; Broad Regional Analysis; Managed EV Charging; Current State of Managed Charging: Progress, Barriers, and Solutions; GSA/EVSE and Managed Charging;

NREL Publication Number

  • NREL/PR-5400-86457


  • electric vehicle
  • EV
  • EV charging
  • EV grid impacts
  • EVs at scale
  • EVSE
  • SCM
  • smart charge management
  • vehicle grid integration
  • VGI


Dive into the research topics of 'Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meeting: May 18, 2023'. Together they form a unique fingerprint.

Cite this