Electric Vehicle Diffusion: Exploring Uncertainties using System Dynamics

Sustainable energy development is an important topic nowadays, where new ways to obtain and use the energy are worldwide researched with a common objective, to mitigate the global warming. Two of the main CO2 polluters are the electricity and the transportation sectors. While some renewable energy technologies are taking place in the electricity sector (e.g. wind, solar and hydraulic), the transportation sector remain stagnant continuing mostly dependent on fossil fuels. Therefore, the request for sustainable mobility is taking high priority for governments, automobile firms and public and private research institutions worldwide. Electric Vehicles (EV) are becoming more attractive nowadays (mainly due to battery evolution) as a sustainable alternative. EV contribute to reduce CO2 emissions, even when charged with electricity generated from fossil fuel (mainly because EV has higher well to wheel efficiency than Internal Combustion Engine (ICE)). On the other hand, if EV are charged from renewable energy then EV will have zero emissions. The objective of this MSc thesis is to develop an insight into the dynamics of the possible diffusion of electric vehicles and find out the uncertainties which can have a significant influence in the EV diffusion. A model is needed to assess the impact of uncertainties in the EV diffusion. Where first, the model can be used to simulate the possible EV diffusion, afterwards the impact on the diffusion can be observed by considering different circumstances where the uncertainties are taken into account. Two different diffusion models are combined in this research, one on a global level (worldwide scope) an another on a local level (country scope, The Netherlands for this research). The global diffusion model creates different conditions to the local diffusion model, therefore the global diffusion model influences some “exogenous” variables of the local diffusion model. Different kind of uncertainties are explored to observe the impact of uncertain conditions on possible diffusion of EV, apart from the different exogenous parameter combinations, uncertain behavior variables and event surprises (e.g. Peak oil prices, new technology surprise, technology breakthrough) are included. The same experiments are also simulated considering EV and Plug-in Hybrid Electric Vehicles (PHEV) as possible technologies to diffuse. In general, PHEV faces less problems to diffuse than EV, mainly because PHEV can take the advantages of ICE (high driving range and the existent infrastructure). The current potential market for PHEV (short, medium and large distance drivers) is bigger than for EV (just short distance drivers, because EV driving range limitation), therefore the expected PHEV diffusion level is also higher than for EV. Furthermore, PHEV diffusion stimulate a natural transition to pure EV if electric infrastructure is provided, where PHEV diffusion make the batteries attributes (price and range) evolve by economies of scale mechanisms. On the other hand the electric demand of PHEV incentives the building of electric infrastructure, and once electric infrastructure is available and the batteries attributes have improved then EV will become highly attractive and a natural transition from PHEV to EV is then expected.