Quantifying the impact of electric vehicles on the electric grid - A simulation based case-study

Arvind Ramanujam, Pandeeswari Sankaranarayanan, Arunchandar Vasan, Rajesh Jayaprakash, Venkatesh Sarangan, Anand Sivasubramaniam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

As the adoption of electric vehicles (EVs) increases, it is important to reliably characterize their recharging load on the electrical grid. Because the last-mile of the electrical grid was never envisioned for EV usage, we need to identify and localize demand-side hot spots due to EV charging. Also, itwould beworthwhile to see howthe EVs can be utilized for the benefit of the grid on activities such as peak reduction and ability to sustain local micro-grids. Quantifying the impacts of EVs on the grid requires an understanding of the spatiotemporal distribution of EVs in a city and the consumption patterns of the EV batteries. These, in turn, depend on the traffic load on the transport grid. In this paper, we attempt to understand these impacts of EV by creating a model of a popular EV (Tesla Model S) and integrating it with SUMO, a broad-based micro traffic simulator. Using this setup, we obtain the EV load on the distribution side of an electrical grid for a real-world traffic pattern dataset from the city of Luxembourg. We find that: (i) The city's aggregate peak demand can be managed within existing levels even when 25% of vehicles become electric. (ii) However, EV charging does overwhelm the distribution network creating hot spots and these hot spots can be clustered together spatially necessitating additional upstream investments. (iii) When EVs feed power back to the grid, simple algorithms can achieve reasonable aggregate peak shaving (~7%) under low EV penetration levels. For higher EV penetration levels, sophisticated EV coordination algorithms are needed. (iv) Under a penetration level of 25%, EVs can potentially sustain micro-grids that serve the entire base load of 13% of the population for a duration of up to 30 minutes.

Original languageEnglish (US)
Title of host publicatione-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems
PublisherAssociation for Computing Machinery, Inc
Pages228-233
Number of pages6
ISBN (Electronic)9781450350365
DOIs
StatePublished - May 16 2017
Event8th ACM International Conference on Future Energy Systems, e-Energy 2017 - Shatin, Hong Kong
Duration: May 16 2017May 19 2017

Publication series

Namee-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems

Other

Other8th ACM International Conference on Future Energy Systems, e-Energy 2017
CountryHong Kong
CityShatin
Period5/16/175/19/17

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Fuel Technology

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    Ramanujam, A., Sankaranarayanan, P., Vasan, A., Jayaprakash, R., Sarangan, V., & Sivasubramaniam, A. (2017). Quantifying the impact of electric vehicles on the electric grid - A simulation based case-study. In e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems (pp. 228-233). (e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3077839.3077854