A Multi-layer Physic-based Model for Electric Vehicle Energy Demand Estimation in Interdependent Transportation Networks and Power Systems

Future smart cities pave the path toward global electrification. This trend affects various networks, including transportation systems. Transportation electrifications will increase the interdependence between power systems and transportation networks. Electric vehicles (EVs) and charging stations are the main coupling components. Although EVs are introduced as economic and sustainable means of transportation, they can lead to both traffic congestion and power line congestion. This book chapter first provides a big picture of interdependent transportation networks and power systems. It then introduces a comprehensive EV load model, which takes into physical aspects of electric vehicles. Then, it evaluates the required battery power by investigating the required power to overcome different real-world mechanical resistances, such as aerodynamic drag. The goal of this study is to introduce a framework that investigates the physics of the EVs, and analyzes the behavior of electric vehicle drivers based on a given real-world dataset. The proposed EV load model is based on historical driving cycles for 1000 EVs, and hence, reflects the behavior of drivers. Sub-primary level is also investigated, i.e., how can different driving cycles affect the EV's charging demand. We evaluate the required battery power by investigating the required power to overcome the aerodynamic drag, rolling resistance, and the force required for a vehicle climbing a hill.