Envisioning a future 100% electrified transportation sector, this paper uses socio-economic, demographic, and geographic data to assess electric energy demand from commuter traffic. We explore the individual mode choices, which allows to create mode-mix scenarios for the entire population, and quantify the electric energy demand for each scenario using technical specifications of battery and electric drives technology in combination with different charging scenarios. Using data sets for New York City, our results highlight the need for infrastructure investments, the usefulness of flexible charging policies, and the positive impact of incentivizing micromobility and mass-transit options. Our model and results are publicly available as interactive dashboard.
@article{arxiv.2211.11581,
title = {Modeling 100% Electrified Transportation in NYC},
author = {Jingrong Zhang and Amber Jiang and Brian Newborn and Sara Kou and Robert Mieth},
journal= {arXiv preprint arXiv:2211.11581},
year = {2023}
}
Comments
Accepted for publication at the 2023 IEEE PES General Meeting