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Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data

This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," [1].

These files include electricity demand profiles for 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], [3], that produces realistic patterns of residential power consumption, validated using metered data, with a resolution of 10 minutes. Households vary in size and number of occupants and the profiles represent total electricity use, in watts.
The files also include in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with the 200 households assuming both Level 1 (1920 W) and Level 2 (6600 W) residential charging infrastructure. The vehicle recharging profiles have been generated using the modeling proposed by Muratori et al. [4], that produces real-world recharging demand profiles, with a resolution of 10 minutes.

[1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming.
[2] M. Muratori, M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni, "A highly resolved modeling technique to simulate residential power demand," Applied Energy, vol. 107, no. 0, pp. 465 - 473, 2013. https://doi.org/10.1016/j.apenergy.2013.02.057
[3] M. Muratori, V. Marano, R. Sioshansi, and G. Rizzoni, "Energy consumption of residential HVAC systems: a simple physically-based model," in 2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA: IEEE, 22-26 July 2012. https//doi.org/10.1109/PESGM.2012.6344950
[4] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, vol. 58, no. 0, pp. 168-177, 2013. https://doi.org/10.1016/j.energy.2013.02.055
- Originated 08/08/2017 by National Renewable Energy Laboratory.

3 Resources

 NameSizeTypeResource Description
 Residential-Profiles.xlsx70995649dataThis file includes electricity demand profiles for 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], [3], that produces realistic patterns of residential power consumption, validated using metered data, with a resolution of 10 minutes. Households vary in size and number of occupants and the profiles represent total electricity use, in watts. This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Please cite as: "Matteo Muratori, Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data, 2017 [1]. Based on modeling reported in [2] and [3]." [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni, "A highly resolved modeling technique to simulate residential power demand, "Applied Energy, vol. 107, no. 0, pp. 465 - 473, 2013. [3] M. Muratori, V. Marano, R. Sioshansi, and G. Rizzoni, "Energy consumption of residential HVAC systems: a simple physically-based model," in 2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA: IEEE, 22-26 July 2012. The author would like to thank G. Rizzoni, M. Moran, R. Sioshansi, B.-A. Schuelke-Leech, and M. Roberts for their contributions on this research and J. Eichman and A. Meintz for their valuable comments. Results are based upon modeling work supported by the National Science Foundation under Grant No. 1029337. This work was supported by the U.S. Department of Energy under Contract No. DE-AC36-08GO28308 with Alliance for Sustainable Energy, LLC, the Manager and Operator of the National Renewable Energy Laboratory. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The views and opinions expressed in this paper are those of the author alone.
 PEV-Profiles-L1.xlsx58956349dataThis file includes in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], that produces real-world recharging demand profiles, with a resolution of 10 minutes. Vehicles are assumed to be 60% battery electric vehicles with 200 miles range and 40% plug-in hybrid electric vehicles with 40 mile all-electric range. Level 1 charging (1920 W) is assumed and the profiles represent total plug-in electric vehicle charging demand, in watts. This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Please cite as: "Matteo Muratori, Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data, 2017 [1]. Based on modeling reported in [2]." [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, vol. 58, no. 0, pp. 168 - 177, 2013. The author would like to thank G. Rizzoni, M. Moran, R. Sioshansi, B.-A. Schuelke-Leech, and M. Roberts for their contributions on this research and J. Eichman and A. Meintz for their valuable comments. Results are based upon modeling work supported by the National Science Foundation under Grant No. 1029337. This work was supported by the U.S. Department of Energy under Contract No. DE-AC36-08GO28308 with Alliance for Sustainable Energy, LLC, the Manager and Operator of the National Renewable Energy Laboratory. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The views and opinions expressed in this paper are those of the author alone.
 PEV-Profiles-L2.xlsx54616201dataThis file includes in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], that produces real-world recharging demand profiles, with a resolution of 10 minutes. Vehicles are assumed to be 60% battery electric vehicles with 200 miles range and 40% plug-in hybrid electric vehicles with 40 mile all-electric range. Level 2 charging (6600 W) is assumed and the profiles represent total plug-in electric vehicle charging demand, in watts. This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Please cite as: "Matteo Muratori, Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data, 2017 [1]. Based on modeling reported in [2]." [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States, " Energy, vol. 58, no. 0, pp. 168 - 177, 2013. The author would like to thank G. Rizzoni, M. Moran, R. Sioshansi, B.-A. Schuelke-Leech, and M. Roberts for their contributions on this research and J. Eichman and A. Meintz for their valuable comments. Results are based upon modeling work supported by the National Science Foundation under Grant No. 1029337. This work was supported by the U.S. Department of Energy under Contract No. DE-AC36-08GO28308 with Alliance for Sustainable Energy, LLC, the Manager and Operator of the National Renewable Energy Laboratory. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The views and opinions expressed in this paper are those of the author alone.

Keywords

NREL energy data residential power demand plug-in electric vehicles PEV charging smart grid demand response recharging battery hybrid Midwest USA consumption renewable energy RE 2009 RECS electricity use grid modernization

Submitted

•  JUN  • 13 2017

National Renewable Energy Laboratory

by , 303.275.2927, Center 5400, ORCID iD 0000-0003-1688-6742

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Cite this dataset:

Muratori, Matteo (2017): Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data. National Renewable Energy Laboratory. https://dx.doi.org/10.7799/1363870

About this dataset

id 69
DOI 10.7799/1363870
status Publicly accessible
last updated 7 months ago

DOE Project

FY17 AOP 2.6.0.402 Systems Research Supporting Standards and Interoperability

Research Areas

  • Buildings Efficiency
  • Energy Analysis
  • Energy Systems Integration
  • Grid Modernization
  • Transportation

Additional Subjects

  • Transmission/Distribution

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