Building power consumption datasets: Survey, taxonomy and future directions
Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes, Amira

TL;DR
This paper surveys existing building power consumption datasets, compares their features, introduces a new anomaly detection dataset, and discusses future directions for dataset improvement and utilization.
Contribution
It provides a comprehensive review and comparison of 31 datasets, introduces the Qatar university dataset, and offers recommendations for future dataset collection and analysis methods.
Findings
Comparison of 31 datasets across multiple features
Introduction of the Qatar university anomaly detection dataset
Recommendations for improving data collection and analysis
Abstract
In the last decade, extended efforts have been poured into energy efficiency. Several energy consumption datasets were henceforth published, with each dataset varying in properties, uses and limitations. For instance, building energy consumption patterns are sourced from several sources, including ambient conditions, user occupancy, weather conditions and consumer preferences. Thus, a proper understanding of the available datasets will result in a strong basis for improving energy efficiency. Starting from the necessity of a comprehensive review of existing databases, this work is proposed to survey, study and visualize the numerical and methodological nature of building energy consumption datasets. A total of thirty-one databases are examined and compared in terms of several features, such as the geographical location, period of collection, number of monitored households, sampling rate…
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