Abstract
In the next decade, charging demand from an increasing number of electric vehicles will require the charging infrastructure to be further developed. However, the planning of an optimal charging infrastructure is a complex problem as it involves representation of charging demand in space and time, interaction with supply through queuing models and optimisation of placements and sizing of charging stations. The paper takes on this challenge by proposing how trip diaries can be used to develop a space–time demand simulator for electric vehicle movements and be integrated with models for optimal locations of charging stations. In the paper, charging demand is integrated with an information-sharing system, which pass waiting time predictions from the system to the users. An approximation of expected waiting time, depending on generic station specific inputs, is derived from queuing theory. The methodology is applied to the city of Copenhagen and it is found that information sharing lead to better utilisation of charging capacity. Even in a situation where 50% of the population share information, the system performance is almost on par with a situation where all agents are informed. The paper underlines the need to for information sharing in the planning of future charging systems.
Original language | English |
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Article number | 122205 |
Journal | Technological Forecasting and Social Change |
Volume | 187 |
Number of pages | 15 |
ISSN | 0040-1625 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Agent-based simulation
- Charging location and sizing
- G/G/c queuing systems
- Information-sharing
- Optimisation
- Transportation modelling