4.7 Article

Quantifying the Long-Term Impact of Electric Vehicles on the Generation Portfolio

期刊

IEEE TRANSACTIONS ON SMART GRID
卷 5, 期 1, 页码 71-83

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2013.2286353

关键词

Electric vehicles; power generation planning; wind power generation

资金

  1. Commission for Energy Regulation
  2. Bord Gais Energy
  3. Bord na Mona Energy
  4. Cylon Controls
  5. EirGrid
  6. Electric Ireland
  7. Energia
  8. EPRI
  9. ESB International
  10. ESB Networks
  11. Gaelectric
  12. Intel
  13. SSE Renewables
  14. UTRC
  15. Science Foundation Ireland [06/CP/E005]

向作者/读者索取更多资源

Electric Vehicles (EVs) charged in a manner that is optimal to the power system will tend to increase the utilization of the lowest cost power generating units on the system, which in turn encourages investment in these preferable forms of generation. Were these gains to be substantial, they could be reflected in future charging tariffs as a means of encouraging EV ownership. However, where the impact of EVs is being quantified, much of the system benefit can only be observed where generator scheduling is performed by unit-commitment based methods. By making use of a rapid, yet robust unit-commitment algorithm, in the context of a capacity expansion procedure, this paper quantifies the impact of EVs for a variety of demand and wind time-series, relative fuel costs and EV penetrations. Typically, the net-cost of EV charging increases with EV penetration and CO2 cost, and falls with increasing wind. Frequently however these relationships do not apply, where changes in an input often lead to step-changes in the optimal plant mix. The impact of EVs is thus strongly dependent on the dynamics of the underlying generation portfolio.

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