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

Abstract

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,"more » 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. [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.« less

Authors:
Publication Date:
Research Org.:
National Renewable Energy Laboratory - Data (NREL-DATA), Golden, CO (United States); National Renewable Energy Laboratory
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1363870
Report Number(s):
69
DOE Contract Number:  
FY17 AOP 2.6.0.402
Resource Type:
Data
Data Type:
Numeric Data
Country of Publication:
United States
Availability:
datacatalog@nrel.gov
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; 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

Citation Formats

Muratori, Matteo. Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data. United States: N. p., 2017. Web. doi:10.7799/1363870.
Muratori, Matteo. Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data. United States. doi:10.7799/1363870.
Muratori, Matteo. Thu . "Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data". United States. doi:10.7799/1363870. https://www.osti.gov/servlets/purl/1363870.
@article{osti_1363870,
title = {Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data},
author = {Muratori, Matteo},
abstractNote = {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. [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. [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.},
doi = {10.7799/1363870},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {6}
}

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Works referenced in this record:

Highly-resolved modeling of personal transportation energy consumption in the United States
journal, September 2013


A highly resolved modeling technique to simulate residential power demand
journal, July 2013


Energy consumption of residential HVAC systems: A simple physically-based model
conference, July 2012


    Works referencing / citing this record:

    A highly resolved modeling technique to simulate residential power demand
    journal, July 2013


    Highly-resolved modeling of personal transportation energy consumption in the United States
    journal, September 2013