Profile of Charging Load on the Grid Due to Plug-in Vehicles

The paper presents a study of the profile of the load imposed on a power system by grid-charging of the onboard battery pack of electric and plug-in hybrid vehicles. The study uses a large database of field-recorded driving cycles stamped with parking times and locations to predict realistic driving habits of drivers in an urban setting. A fuzzy-logic inference system is designed to emulate the decision-making process of a driver when deciding to charge the vehicle's battery. The charging load is then estimated on an hourly basis for a number of electric and plug-in hybrid vehicles with different storage capacities. Level-1 and level-2 charging regimes as well as two scenarios for charging, namely charging at home and charging at home and work, are considered. The load profile is presented as an hourly probability of charging for each vehicle type. The results demonstrate how penetration of plug-in hybrid and electric vehicles affects the load on a utility network.

[1]  Edward Ungar,et al.  Plug In, Turn On, and Load Up , 2010, IEEE Power and Energy Magazine.

[2]  Ryan Smith,et al.  Characterization of urban commuter driving profiles to optimize battery size in light-duty plug-in electric vehicles , 2011 .

[3]  P.H.L. Notten,et al.  Adaptive Battery Management Systems for the new generation of Electrical Vehicles , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.

[4]  J. Voelcker.  How Green Is My Plug-In? , 2009, IEEE Spectrum.

[5]  Jeff Tollefson,et al.  Car industry: Charging up the future , 2008, Nature.

[6]  Ali Emadi,et al.  Modern electric, hybrid electric, and fuel cell vehicles : fundamentals, theory, and design , 2009 .

[7]  W. Short,et al.  Evaluation of Utility System Impacts and Benefits of Optimally Dispatched Plug-In Hybrid Electric Vehicles (Revised) , 2006 .

[8]  Kevin P. Schneider,et al.  Impacts Assessment of Plug-in Hybrid Vehicles on Electric Utilities and Regional US Power Grids: Part 1: Technical Analysis , 2007 .

[9]  Richard Watts Mr..  Effects of Plug-in Hybrid Electric Vehicles on Vermont Electric Transmission System , 2009 .

[10]  Ali Emadi,et al.  Modeling and Simulation of Electric and Hybrid Vehicles , 2007, Proceedings of the IEEE.

[11]  David Wenzhong Gao,et al.  Plug-in Hybrid Electric Vehicle Control Strategy Parameter Optimization , 2008 .

[12]  Tony Markel,et al.  Costs and Emissions Associated with Plug-In Hybrid Electric Vehicle Charging in the Xcel Energy Colorado Service Territory , 2007 .

[13]  E. H. Mamdani,et al.  Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis , 1976, IEEE Transactions on Computers.

[14]  Stanton W. Hadley,et al.  Potential Impacts of Plug-in Hybrid Electric Vehicles on Regional Power Generation , 2009 .

[15]  Ali Elkamel,et al.  Optimal Transition to Plug-In Hybrid Electric Vehicles in Ontario, Canada, Considering the Electricity-Grid Limitations , 2010, IEEE Transactions on Industrial Electronics.

[16]  A. Frank.  Plug-in hybrid vehicles for a sustainable future , 2007 .

[17]  T D Gillespie,et al.  Fundamentals of Vehicle Dynamics , 1992 .

[18]  Ali Emadi,et al.  Modeling and Simulation of Electric and Hybrid Vehicles Tools that can model embedded software as well as components, and can automate the details of electric and hybrid vehicle design, need to be developed. , 2007 .

[19]  Tony Markel,et al.  Field Testing Plug-In Hybrid Electric Vehicles with Charge Control Technology in the Xcel Energy Territory , 2009 .

[20]  Shaahin Filizadeh,et al.  Statistical Development of a Duty Cycle for Plug-in Vehicles in a North American Urban Setting Using Fleet Information , 2010, IEEE Transactions on Vehicular Technology.