Javascript must be enabled for the correct page display

STECCAR: Simulating the Transition to Electric Cars Using the Consumat Agent Rationale

Kangur, A.M.A. (2014) STECCAR: Simulating the Transition to Electric Cars Using the Consumat Agent Rationale. Master's Thesis / Essay, Artificial Intelligence.

[img]
Preview
Text
AI-MAI-2014-A.M.A.Kangur.pdf - Published Version

Download (6MB) | Preview
[img] Text
toestemming.pdf - Other
Restricted to Backend only

Download (22kB)

Abstract

This thesis presents the STECCAR model: a newly developed agent-based model of the Dutch consumer car market, constructed to study the diffusion of electric vehicles in the Netherlands. In agent-based modelling, the micro-level characteristics of numerous, often heterogeneous, agents are initialised, and the emerging macro-level behaviour of the population is studied. The underlying rationale of the agents in our model is structured through the Consumat approach; a cognitive framework based on theories from psychology and economics. Within this approach, agents are defined by their individual needs, abilities, decision-making process, and personality. The results of 1.795 survey respondents were used to initialise each individual agent after a Dutch citizen with its own characteristics and driving behaviour. At the shared car market, agents may purchase gasoline vehicles, plug-in hybrid electric vehicles and battery-electric vehicles. Each fuel technology comes with its own functional and financial characteristics. Mimicking the actual Dutch car market, three types of agents are defined using the input survey: lessees, purchasers of new vehicles, and occasion buyers. Within this context, the first two agent types determine the supply of cars to the occasion market. Validation of the model is performed using recent consumer data about Dutch yearly sale figures, occasion market size, ownership characteristics and scrappage data. The model is subsequently used to study the effects of different policies and technological advancements on the diffusion process of electric vehicles. Some of the specific findings include that 'bijtelling' policy has a strong regulatory effect on the diffusion of electric cars and that a rapid realization of a nation-wide fast charge network is an important step towards making battery-electric vehicles competitively attractive. More generally, simulations using the STECCAR model show that the effect of measures can be strengthened by combining measures, or by applying them in a specific temporal order. Additionally, targeting measures at battery-electric vehicles specifically, but not at plug-in hybrid electric vehicles, could lead to a larger overall reduction in carbon emissions. Long term scenarios show that a quick diffusion of electric vehicles results in unconventional behaviour on the occasion market. We conclude that agent-based models can provide unique and valuable insights into how to influence complex relations within interactive social systems, such as the Dutch car market. Implications of using an agent-based model to study the diffusion of electric cars are described. Regarding agent-based modelling in general, the importance of proper validation and the benefits of using a psychologically-founded cognitive framework are discussed.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Artificial Intelligence
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:02
Last Modified: 15 Feb 2018 08:02
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/12386

Actions (login required)

View Item View Item