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Title: Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users
Abstract

Problems of poor network interoperability in electric vehicle (EV) infrastructure, where data about real-time usage or consumption is not easily shared across service providers, has plagued the widespread analysis of energy used for transportation. In this article, we present a high-resolution dataset of real-time EV charging transactions resolved to the nearest second over a one-year period at a multi-site corporate campus. This includes 105 charging stations across 25 different facilities operated by a single firm in the U.S. Department of Energy Workplace Charging Challenge. The high-resolution data has 3,395 real-time transactions and 85 users with both paid and free sessions. The data has been expanded for re-use such as identifying charging behaviour and segmenting user groups by frequency of usage, stage of adoption, and employee type. Potential applications include but are not limited to simulating and parameterizing energy demand models; investigating flexible charge scheduling and optimal power flow problems; characterizing transportation emissions and electric mobility patterns at high temporal resolution; and evaluating characteristics of early adopters and lead user innovation.

Authors:
; ;
Award ID(s):
1945332 1931980
Publication Date:
NSF-PAR ID:
10272953
Journal Name:
Scientific Data
Volume:
8
Issue:
1
ISSN:
2052-4463
Publisher:
Nature Publishing Group
Sponsoring Org:
National Science Foundation
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