In the Smart Grid environment, the advent of intelligent measuring devices facilitates monitoring appliance electricity consumption. This data can be used in applying Demand Response (DR) in residential houses through data analytics, and developing data mining techniques. In this research, we introduce a smart system foundation that is applied to user's disaggregated power consumption data. This system encourages the users to apply DR by changing their behaviour of using heavier operation modes to lighter modes, and by encouraging users to shift their usages to off-peak hours. First, we apply Cross Correlation (XCORR) to detect times of the occurrences when an appliance is being used. We then use The Dynamic Time Warping (DTW) to recognize the operation mode used.
@article{arxiv.2008.02908,
title = {Demand Response For Residential Uses: A Data Analytics Approach},
author = {Abdelkareem Jaradat and Hanan Lutfiyya and Anwar Haque},
journal= {arXiv preprint arXiv:2008.02908},
year = {2020}
}
Comments
6 pages, 8 figures, IEEE World Forum on Internet of Things 2020