Using real mobility patterns to assess the impact of 100% electrified mobility in a German city

Author:

Klingert Sonja,Lee Jong-Won

Abstract

AbstractUntil now, individual motorized mobility has been almost exclusively powered by fossil energy sources. The battle against climate change, however, requires a transformation of the mobility system with the ultimate objective of a full electrification of transport. Ultimately, this will increase considerably the load on the distribution grid both in overall size and through temporarily and locally distributed charging. This paper explores the effects of an assumed full electrification of individual motorized transport on the power grid in a major German city using real traffic data collected from a German traffic panel and employing a microscopic and dynamic travel simulation with the Simulation of Urban MObility tool. The main finding of the traffic simulation is that the local and temporary impact on the distribution grid is very sensitive to the distribution of charging stations and their geographical aggregation in transformers. However, behavior change in the form of charging at different points in time and locations or using less power can alleviate local peaks, up to 50% in the simulated scenario. Therefore, this paper addresses the previously uncovered need for a more profound and realistic computation that includes all important aspects of a proper traffic simulation. It further extends the barely covered field of dynamic simulations that operate on real mobility data. With that, limitations arise from the process of transposing driving data into geographical data as it is very sensitive to underlying assumptions. However, we are convinced that the spatialization of charging stations and the randomization of trip assignments represent the most transparent and meaningful way of overcoming these limiting factors.

Funder

Universität Mannheim

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Energy Engineering and Power Technology,Information Systems

Reference36 articles.

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2. Research on new energy vehicle charging prediction based on Monte Carlo algorithm and its impact on distribution network;Frontiers in Energy Research;2023-11-16

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