Datasets
Open Access
GEM HOUSE openData: German Electricity consumption in Many HOUSEholds over three years 2018-2020 (Fresh Energy)
- Citation Author(s):
- Submitted by:
- Filip Milojkovic
- Last updated:
- Mon, 09/20/2021 - 04:54
- DOI:
- 10.21227/4821-vf03
- Data Format:
- License:
3542 Views- Categories:
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Abstract
We welcome any use of this openData package. For any questions or inquiries please get in touch with filip.milojkovic .at. beenera.de
This publication is part of a research and development project with the goal to provide households with data driven and user centered value added services around smart meter data in a native app. Fresh Energy GmbH publishes the GEM HOUSE openData package under the Open Data Commons Open Database License (ODbL). The delivery contains daily electricity consumption data for 955 households and additional information for a subsample of households, which includes meta data (such as a user-generated list of appliances and the number of occupants), high resolution data (0,5Hz) and results from non-intrusive appliance load monitoring (NILM), also known as algorithmic disaggregation. This paper shows descriptive data analysis with tables and graphs to provide the analyst with a first glance at the scope and depth of the content, as well as a codebook with variable definitions.
Instructions:
For a documentation of the content in GEM HOUSE openData please consult the paper. The scripts for generating an RData object and the paper can be accessed here as well (you may have to log in). Single file access is available on this web-frontend. For a more convenient access to data on the AWS S3 bucket you first need to register with IEEE free of charge (apply promotion code DATAPORT1, credit card details are necessary, please also consult the faq https://supportcenter.ieee.org/app/answers/detail/a_id/3187/kw/dataport). Log in to your account and renew your AWS credentials. Those can be used to download the full data via any AWS S3 client (such as cyberduck, cloudberry or cross ftp).
For convenient handling of this project, please download GEM-HOUSE-R-project.zip, which contains all code, text, data and graphs well sorted and ready to load into R-Studio (this does not include high-res data).
Dataset Files
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- household-information.csv (96.15 kB)
- raw-NILM.zip (36.52 MB)
- summary2.csv (75.50 kB)
GEM-HOUSE-paper-R-markdown.Rmd (37.32 kB)
01_make-RData.R (9.52 kB)
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Documentation
| Attachment | Size |
|---|---|
 GEM-HOUSE-paper-Milojkovic-v1.0.pdf | 6.46 MB |
Comments
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