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Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation

Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation

Rashid A. Waraich, Gil Georges, Matthias D. Galus, Kay W. Axhausen
Copyright: © 2014 |Pages: 37
ISBN13: 9781466649200|ISBN10: 1466649208|EISBN13: 9781466649217
DOI: 10.4018/978-1-4666-4920-0.ch014
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MLA

Waraich, Rashid A., et al. "Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation." Data Science and Simulation in Transportation Research, edited by Davy Janssens, et al., IGI Global, 2014, pp. 282-318. https://doi.org/10.4018/978-1-4666-4920-0.ch014

APA

Waraich, R. A., Georges, G., Galus, M. D., & Axhausen, K. W. (2014). Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation. In D. Janssens, A. Yasar, & L. Knapen (Eds.), Data Science and Simulation in Transportation Research (pp. 282-318). IGI Global. https://doi.org/10.4018/978-1-4666-4920-0.ch014

Chicago

Waraich, Rashid A., et al. "Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation." In Data Science and Simulation in Transportation Research, edited by Davy Janssens, Ansar-Ul-Haque Yasar, and Luk Knapen, 282-318. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4920-0.ch014

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Abstract

Battery-electric and plug-in hybrid-electric vehicles are envisioned by many as a way to reduce CO2 traffic emissions, support the integration of renewable electricity generation, and increase energy security. Electric vehicle modeling is an active field of research, especially with regards to assessing the impact of electric vehicles on the electricity network. However, as highlighted in this chapter, there is a lack of capability for detailed electricity demand and supply modeling. One reason for this, as pointed out in this chapter, is that such modeling requires an interdisciplinary approach and a possibility to reuse and integrate existing models. In order to solve this problem, a framework for electric vehicle modeling is presented, which provides strong capabilities for detailed electricity demand modeling. It is built on an agent-based travel demand and traffic simulation. A case study for the city of Zurich is presented, which highlights the capabilities of the framework to uncover possible bottlenecks in the electricity network and detailed fleet simulation for CO2 emission calculations, and thus its power to support policy makers in taking decisions.

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