Abstract
A key challenge for the roll-out of public charging infrastructure is that electric vehicles are needed to function both as a clean mode of transportation and as part of a sustainable electricity system, while being cost-effective. Translating these high-level policy goals to a coherent roll-out strategy is not trivial. We address this by analyzing local charging behavior and linking behavior indicators to specific policy measures through a decision tree. We analyze how policy measures for: (1) increasing the number of charge points, (2) reducing hogging, (3) vehicle-to-grid, (4) overnight charging, and (5) solar charging align with overall goals and characteristics of specific neighborhoods. More specifically, we analyze a dataset containing one million charging sessions in the Netherlands, and (1) link this data to neighborhood characteristics and (2) evaluate the coherency of policy mixes. Our analysis shows great spatial variation in charging behavior and consequently in the suitable policy mixes.
Original language | English |
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Article number | 102452 |
Number of pages | 19 |
Journal | Transportation Research. Part D: Transport and Environment |
Volume | 85 |
DOIs | |
Publication status | Published - Aug 2020 |
Funding
This work was supported by the Uncertainty Reduction in Smart Energy Systems (URSES) research program funded by the Dutch organization for scientific research (NWO) and Shell under the project Realizing the smart grid: aligning consumer behaviour with technological opportunities (SMARTER) with grant number 408-13-009. The funding sources had no involvement in the study beyond funding of the research project.
Keywords
- Charge point hogging
- Charging infrastructure
- Electric vehicle
- Policy mix
- Smart charging
- Vehicle-to-grid