Probabilistic Modeling and Statistical Analysis of Aggregated Electric Vehicle Charging Station Load

Abstract

The number of electric vehicles is increasing worldwide. The charging of a single electric vehicle can draw several kilowatts of power, and the aggregate effects of charging thousands of electric vehicles on electric power system infrastructure, operation, and planning must be considered. An important tool in studying the integration of electric vehicles and developing associated technologies and controls within the framework of the smart grid are probabilistic models of charging station load. This article identifies, evaluates, and proposes probabilistic models and analyzes the statistical characteristics of aggregated electric vehicle charging station load. A data-driven approach is taken, using measured time-stamped power consumption from charging stations to formulate and evaluate suitable parametric probabilistic models. The influence of time-of-use pricing on electric vehicle charging station load characteristics is also examined. Two data sets—one from Washington State, the other from San Diego, CA—each covering over 2 years, are used to create the models.

Keywords:

• charging stations
• electric vehicles
• goodness-of-fit
• load duration curve
• probabilistic modeling
• smart grid
• time-of-use pricing

Additional information

Notes on contributors

Henry M. Louie

Henry M. Louie received his B.S.E.E. from Kettering University in 2002, his M.S. from the University of Illinois at Urbana-Champaign in 2004, and his Ph.D. in electrical engineering from University of Washington in 2008. He is currently an associate professor in the Department of Electrical and Computer Engineering at Seattle University. In 2015/2016, he will be a Fulbright Scholar to the Copperbelt University in Kitwe, Zambia. He is a senior member of the IEEE. His fields of interest include statistical and probabilistic modeling of stochastic sources and loads and energy development in less economically developed countries.