This dataset was created by inserting anomalies, following the methodology described in H. Rashid, P. Singh, V. Stankovic and L. Stankovic, "Can Non-Intrusive Load Monitoring be used for Identifying an Appliance's Anomalous Behaviour", Applied Energy, Jan 2018, in the measured power traces of seven household electrical load measurements, taken from the following publicly available datasets: (i) Houses 115, 439, 490, 1463, and 3538 from the Dataport dataset (https://www.pecanstreet.org/), (ii) house iawe_home from iAWE dataset (http://iawe.github.io/) and (iii) house 6 from the REDD dataset (http://redd.csail.mit.edu/). This dataset is useful in understanding the effect on anomalous appliance behaviour on energy consumption, especially for compressor-based appliances with a significant energy footprint.
When using this dataset please cite the following paper in Elsevier Applied Energy, H. Rashid, P. Singh, V. Stankovic and L. Stankovic, "Can Non-Intrusive Load Monitoring be used for Identifying an Appliance's Anomalous Behaviour", Applied Energy, Jan 2018
Date made available | 18 Jan 2019 |
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Publisher | University of Strathclyde |
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Date of data production | 2017 - 2018 |
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Geographical coverage | India and USA |
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