TY  - CONF
T1  - A Socio-Psychological Modal Choice Approach to Modelling Mobility and Energy Demand for Electric Vehicles
A1  - Nguyen, Khoa
A1  - Schumann, René
ED  - Nguyen, Khoa
ED  - Roman, Rudel
ED  - Schumann, René
JA  - Energy Informatics
TI  - Proceedings of the 9th DACH  Conference on Energy Informatics
T3  - Energy Informatics
Y1  - 2020
VL  - 3
PB  - Springer
UR  - https://energyinformatics.springeropen.com/articles/10.1186/s42162-020-00123-7
M2  - doi: https://doi.org/10.1186/s42162-020-00123-7
KW  - Agent-based modelling
KW  - Agent-based modelling · Modal choice simulation · Multi- agent system · Behavioural theory
KW  - Electric Vehicle
KW  - Modal choice simulation
N2  - The development of efficient electric vehicle (EV) charging infrastructure requires modelling of consumer demand at an appropriate level of detail. Since only limited information about real customers is available, most simulations employ a stochastic approach by combining known or estimated business features (e.g. arrival and departure time, requested amount of energy) with random variations. However, these models in many cases do not include factors that deal with the social characteristics of EV users, while others do not emphasise on the economic elements. In this work, we introduced a more detailed demand model employing a modal choice simulation framework based on Triandis’ Theory of Interpersonal Behaviour, which can be calibrated by empirical data and is capable of combining a diverse number of determinants in human decision-making. By applying this model on Switzerland mobility domain, an analysis on three of the most popular EV incentives from both supply and demand sides is provided, which aims for a better understanding of electro-mobility systems by relating its causes and effects.
ER  -