Transport-based load modeling and sliding mode control of plug-in electric vehicles for robust renewable power tracking

This paper develops a modeling and control paradigm for the aggregate charging dynamics of plug-in electric vehicles (PEVs). The central goal of the paper is to derive a control policy that can adapt the aggregate charging power of PEVs to highly intermittent renewable power. The key assumption here is that the grid is able to directly control the charging power of PEVs in real-time, through broadcasting a universal control signal. Using the transport-based load modeling principle, we develop a partial differential equation model for the collective charging of PEVs. We use real driving data to simulate the model and validate it against a PEV Monte Carlo simulation model. Adopting the sliding mode control theory, we then develop a robust output tracking controller for the system. The controller uses the real-time error between power supply and demand as the only measured signal, and attempts to suppress it despite the variation of the population of PEVs on the grid. We examine the performance of the controller using numerical simulations on a real wind power trajectory.