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Forecasting the Impact of Plug-In Hybrid Electric Vehicles Penetration on Ontario’s Electricity Grid

[+] Author Affiliations
Lena Ahmadi, Eric Croiset, Ali Elkamel, Peter L. Douglas

University of Waterloo, Waterloo, ON, Canada

Woramon Unbangluang, Hong-Ming Ku

King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

Evgueniy Entchev

CANMET Energy Technology Centre, Natural Resource Canada, Ottawa, ON, Canada

Paper No. IMECE2010-38240, pp. 721-730; 10 pages
doi:10.1115/IMECE2010-38240
From:
  • ASME 2010 International Mechanical Engineering Congress and Exposition
  • Volume 11: New Developments in Simulation Methods and Software for Engineering Applications; Safety Engineering, Risk Analysis and Reliability Methods; Transportation Systems
  • Vancouver, British Columbia, Canada, November 12–18, 2010
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4448-9
  • Copyright © 2010 by ASME

abstract

Vehicle emissions are a major concern in the development of new automobiles. Plug-in hybrid electric vehicles (PHEVs) have a large potential to reduce greenhouse gases emissions and increase fuel economy and fuel flexibility. PHEVs are propelled by the energy from both gasoline and electric power sources. Penetration of PHEVs into the automobile market affects the electrical grid and increasing the electricity demand has not been fully investigated. This paper studies effects of the wide spread adoption of PHEVs on peak and base load demands in Ontario, Canada. Long-term forecasting models of peak and base load demands and the number of light-duty vehicles sold are developed. To create proper forecasting models, both linear regression (LR) and non-linear regression (NLR) techniques are employed, considering different ranges in the demographic, climate and economic variables. The results from the LR and NLR models (LRM and NLRM) are compared and the most accurate one is selected. Furthermore, forecasting the effects of PHEVs penetration is done through consideration of various scenarios of penetration levels, such as mild, normal and aggressive ones. Finally, the additional electricity demand on the Ontario electricity grid from charging PHEVs is incorporated for electricity production planning purposes.

Copyright © 2010 by ASME

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