Abstract

Transportation sector in Switzerland is the largest domestic greenhouse gas (GHG) emitter. Hence it has the potential to benefit from the plug-in hy-brid electric vehicles (PHEVs) introduction. To assess the effect of PHEVs penetration, it is crucial to establish an appropriate model which is able to reflect the realistic driving patterns. Through this project, therefore, a stochastic modeling of the PHEVs penetration for Swiss traffic is done. Although there exists several traffic models, the model developed in this project is distinguished by the possibility of using two real-life stochastic variables; departure time and trip distance. By using the variables within a discrete-time non-Markovian process, it is possible to emulate the realis-tic randomness. As a result, an aggregated daily mobility pattern for whole fleet is acquired, and daily probabilities for “Driving ” state and four different “Parked ” states are also generated. From these probabilities, the probabili-ties of state transition are obtained as well. Also, to acquire power demand,