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

Abstract

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 microsimulator's architecture, and its ability to scale various abstraction levels depending on the accuracy needed, study objective, and computational time and resources.

A Novel Optimization of Plug-In Electric Vehicles Charging and Discharging Behaviors in Electrical Distribution Grid

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A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles

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