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The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea
AMI has been gradually replacing conventional meters because newer models can acquire more informative energy consumption data. The additional information has enabled significant advances in many fields, including energy disaggregation, energy consumption pattern analysis and prediction, demand resp...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783544/ https://www.ncbi.nlm.nih.gov/pubmed/31594953 http://dx.doi.org/10.1038/s41597-019-0212-5 |
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author | Shin, Changho Lee, Eunjung Han, Jeongyun Yim, Jaeryun Rhee, Wonjong Lee, Hyoseop |
author_facet | Shin, Changho Lee, Eunjung Han, Jeongyun Yim, Jaeryun Rhee, Wonjong Lee, Hyoseop |
author_sort | Shin, Changho |
collection | PubMed |
description | AMI has been gradually replacing conventional meters because newer models can acquire more informative energy consumption data. The additional information has enabled significant advances in many fields, including energy disaggregation, energy consumption pattern analysis and prediction, demand response, and user segmentation. However, the quality of AMI data varies significantly across publicly available datasets, and low sampling rates and numbers of houses monitored seriously limit practical analyses. To address these challenges, we herein present the ENERTALK dataset, which contains both aggregate and per-appliance measurements sampled at 15 Hz from 22 houses. Among the publicly available datasets with both aggregate and per-appliance measurements, 15 Hz was the highest sampling rate. The number of houses (22) was the second-largest where the largest one had a sampling rate of 1 Hz. The ENERTALK dataset is also the first Korean open dataset on residential electricity consumption. |
format | Online Article Text |
id | pubmed-6783544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67835442019-10-10 The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea Shin, Changho Lee, Eunjung Han, Jeongyun Yim, Jaeryun Rhee, Wonjong Lee, Hyoseop Sci Data Data Descriptor AMI has been gradually replacing conventional meters because newer models can acquire more informative energy consumption data. The additional information has enabled significant advances in many fields, including energy disaggregation, energy consumption pattern analysis and prediction, demand response, and user segmentation. However, the quality of AMI data varies significantly across publicly available datasets, and low sampling rates and numbers of houses monitored seriously limit practical analyses. To address these challenges, we herein present the ENERTALK dataset, which contains both aggregate and per-appliance measurements sampled at 15 Hz from 22 houses. Among the publicly available datasets with both aggregate and per-appliance measurements, 15 Hz was the highest sampling rate. The number of houses (22) was the second-largest where the largest one had a sampling rate of 1 Hz. The ENERTALK dataset is also the first Korean open dataset on residential electricity consumption. Nature Publishing Group UK 2019-10-08 /pmc/articles/PMC6783544/ /pubmed/31594953 http://dx.doi.org/10.1038/s41597-019-0212-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Shin, Changho Lee, Eunjung Han, Jeongyun Yim, Jaeryun Rhee, Wonjong Lee, Hyoseop The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title | The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title_full | The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title_fullStr | The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title_full_unstemmed | The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title_short | The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea |
title_sort | enertalk dataset, 15 hz electricity consumption data from 22 houses in korea |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783544/ https://www.ncbi.nlm.nih.gov/pubmed/31594953 http://dx.doi.org/10.1038/s41597-019-0212-5 |
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