Analysis of the energy storage operation of electrical vehicles with a photovoltaic roof using a Markov chain model

Energy storage operation in electrical vehicles, with a photovoltaic roof, is analyzed. When an electrical vehicle uses a photovoltaic roof in order to provide supplemental power, it is critical to understand how much power is generated through insolation and how generated photovoltaic power affects the energy storage operation of the electrical vehicles. Hence, this paper proposes to use a Markov chain model in order to simulate the charge and discharge processes that occur in energy storage, which enables to estimate the charge level of energy storage system at the end of any day. From a planning perspective, the aforementioned estimations may take an important role; for instance, the simulated results may help to answer questions such as how much power would be required from grid operators as a number of operating electrical vehicles increase in a certain region. In order to conduct the simulations, this paper uses insolation data collected in Austin, TX, USA and survey results on how far people drive every day in the urban cluster areas in the USA. The data sets are used to determine their distributions so that a large number of random values can be generated with respect to the found distribution using Monte Carlo simulations. Then, the generated random values are used to determine the one-step transition probability matrices that represent charge and discharge processes. In addition, the energy storage system of an electrical vehicle model developed by Daimler is used to demonstrate the presented Markov chain model and estimate the expected charge level of energy storage system at the end of any day.