A hierarchical networked micro-simulator to study grid-integration of renewables and electric vehicles

The effect of integrating intermittent renewable generation such as wind and solar, as well as plug-in electric vehicles (PEVs) on a grid is an important area of study. Renewable generation depends on weather. Energy consumption, storage, and emergency usage of battery-stored power in PEVs are dependent on the spread of such vehicles in a geographical area, commute patterns, and hours of long-term parking. These are stochastic in nature. We have developed a hierarchical networked micro-simulation environment to characterize their effect on the grid's load-carrying capacity, reliability of unit commitment and planning, and boundaries of grid safety, etc. We have used this micro-simulation environment for a number of studies based on 4-year real data from New York City's weather and load profiles, projected PEV population, and current commute profiles. In this paper, we describe our micro-simulator's architecture, and its ability to scale various abstraction levels depending on the accuracy needed, study objective, and computational time and resources.