@misc{a303b67cbb5a4621aefe810925595f48,
title = "Scaled Implementation of Smart Charge Management for Electric Vehicles",
abstract = "Smart charge management (SCM) has become a critical strategy for mitigating potential grid impacts and reducing electricity costs for all customers. This study will evaluate the economics of implementing light-duty EV SCM at scale across the United States. This work will enhance distribution system analysis by estimating SCM implementation costs, exploring viable business cases, and developing a framework for national-level applications. The primary methodology involves leveraging detailed grid modeling from a specific service territory and using spatial extrapolation techniques to generalize findings to other regions. The analysis will develop key metrics to quantify the costs and benefits of SCM, including implementation costs relative to strategy and scale, the cost of distribution system upgrades with and without SCM, and the percentage of peak-load reduction. The objective is to produce a comprehensive report and a parameterized framework that enables utilities to self-assess the value of SCM in their own service territories. This will support the development of cost-effective charging strategies, accelerate the energization of new EV chargers, and facilitate the seamless integration of EVs into the nation's power grid.",
keywords = "cost-benefit analysis, distribution system planning, electric vehicles, grid impacts, smart charge management, spatial extrapolation, utility planning, vehicle-grid integration",
author = "Nadia Panossian and Dongjoo Kim and Tarek Elgindy and Yanning Li and Eric Wood and Nazib Siddique and Kumar Jhala and Kiran Kumar and Zhou, \{Yan (Joann)\}",
year = "2026",
doi = "10.66816/pr5192221",
language = "American English",
series = "Presented at the DOE Transportation Technologies Program 2026 Annual Merit Review (AMR) and Peer Evaluation Meeting, 1-4 June 2026, Arlington, Virginia",
type = "Other",
}