@inproceedings{10.1145/3307772.3328317,
author = {Nadeem, Ahmad and Arshad, Naveed},
title = {PRECON: Pakistan Residential Electricity Consumption Dataset},
year = {2019},
isbn = {9781450366717},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3307772.3328317},
doi = {10.1145/3307772.3328317},
abstract = {Buildings consume on average of over 40% of energy throughout the world[1]. Therefore, it is crucial to fully understand the consumption behaviour of building occupants for energy efficiency, efficient load balancing and better demand-side management. To this end, small number of datasets are available from developing countries, particularly South Asia, that can model consumption behaviours of a wide range of residential electricity users. In this paper, we present PRECON dataset, collected over a period of one year, of electricity consumption patterns for 42 residential properties having varied demographics. Data is collected for the whole house consumption and from high powered devices as well as from major areas of the building. This dataset can play a pivotal role for distribution companies and policymakers to use data-driven optimization of generation, perform better demand-side management and improve energy efficiency.},
booktitle = {Proceedings of the Tenth ACM International Conference on Future Energy Systems},
pages = {52–57},
numpages = {6},
keywords = {Consumption, Electricity, PRECON, Dataset},
location = {Phoenix, AZ, USA},
series = {e-Energy '19}
}