Anton, Laurențiu Lucian (Reykjavik University), Cicic, Mladen (University of California, Berkeley), Kristjánsson, Ragnar (Reykjaví University)

Traffic-Based Demand Modeling for EV Fast-Charging Stations: A Case Study in Iceland

Scheduled for presentation during the Invited Session "Sustainable Electrified Road Transportation" (ThAT3), Thursday, September 26, 2024, 10:30−10:50, Salon 6

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 7, 2024

Abstract

The rapid adoption of electric vehicles (EVs) in Iceland has led to measurable impacts on the country’s electricity system. There is a pressing need to model the interplay between traffic dynamics and power demand as seen by the grid, particularly at public charging locations. This paper presents a methodology for developing demand profiles for Fast-Charging Service Stations (FCSS) from traffic dynamics. An Open Source Python package is built and distributed, enabling users to conduct electromobility studies without requiring in-depth knowledge of the underlying numerical simulator. The package implements a customizable multi-class macroscopic electromobility model, linking traffic flows to expected demand profiles at FCSS locations along the road. A case study in Iceland is presented, where expected power demand at strategic FCSS locations along the Highway 1 route between Reykjavik and Akureyri are generated for various EV adoption scenarios, considering both passenger vehicles and heavy-duty vehicles. Traffic data is provided by the Icelandic Road Administration, FCSS locations are advised by the Icelandic National Energy Authority, and peak demand thresholds are advised by the Icelandic Transmission System Operator. This case study is intended as a tutorial for similar future studies in other jurisdictions.