Abstract
The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.
Original language | American English |
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Number of pages | 6 |
DOIs | |
State | Published - 2024 |
Event | 2024 IEEE Transportation Electrification Conference & Expo - Rosemont, IL, USA Duration: 19 Jun 2024 → 21 Jun 2024 |
Conference
Conference | 2024 IEEE Transportation Electrification Conference & Expo |
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City | Rosemont, IL, USA |
Period | 19/06/24 → 21/06/24 |
Bibliographical note
See NREL/CP-5400-89286 for preprintNREL Publication Number
- NREL/CP-5400-91038
Keywords
- data-driven analysis
- light-duty electric vehicle
- residential charging demand