Illustration of the dataset: this 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.
Unit of the dataset: this file represents the total power comsumption, which is in unit of walt.
Axis of abscissas: 200 electricity meters
Axis of ordinate: 365 days
Label: abnormal value of each electricity meter >= mean + 3 * standard deviation
ResidentialProfiles_days is the original data
ResidentialProfiles_days_label is the abnormal label, where 0 represents normal, and 1 represents abnormal
URL of the dataset: https://data.nrel.gov/submissions/69
URL of the research paper: https://www.nature.com/articles/s41560-017-0074-z
The original illustration of the dataset of smart electricity meter: (https://data.nrel.gov/submissions/69)
This 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.