Residential electrical loads measurements with simulated anomalies in air conditioner and refrigerator

Dataset

Description

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 available18 Jan 2019
PublisherUniversity of Strathclyde
Date of data production2017 - 2018
Geographical coverageIndia and USA

Cite this

Rashid, H. (Creator), Singh, P. (Supervisor), Stankovic, V. (Contributor), Stankovic, L. (Data Manager). (18 Jan 2019). Residential electrical loads measurements with simulated anomalies in air conditioner and refrigerator. University of Strathclyde. cods_comad_dataset_20190118T104959Z_001(.zip), README(.txt). 10.15129/d712ccac-21a1-40d2-8456-41217b62a6d5