Title
Establishment of Enhanced Load Modeling by Correlating With Occupancy Information
Publication Date
3-2020
Document Type
Article
Abstract
Over the past decades, ther have been an increased number of the Internet of Things (IoT) sensor deployment in electrical distribution networks. This paper proposes a statistical approach to establish the correlations between estimated occupancy within physical proximity and the associated loads. This study includes a sensitivity analysis of occupancy and how it influences load consumptions. First, a statistical distribution with a regression model is formed to correlate these two heterogeneous properties, in terms of occupancy and power (OP) consumption, to generate a time-dependent model. Since model deviations from an estimate based on regular pattern as a time-varying process with the curve fitting, the possible structural deviations in real-time demand are then considered to update the initial regression model using new real-time estimates and observations obtained every demanded time duration. The dynamic profile of human movements and their load characteristics are established with parametric adjustments and observed using the case studies.
Publication Title
IEEE Transactions on Smart Grid
Volume
11
Issue
2
First Page
1703
Last Page
1713
DOI
10.1109/TSG.2019.2942581
Publisher Policy
Pre-print, post-print
Open Access Status
Licensed
Recommended Citation
Tang, Y., Zhao, S., Ten, C.-W., Zhang, K., & Logenthiran, T. (2020). Establishment of Enhanced Load Modeling by Correlating With Occupancy Information. IEEE Transactions on Smart Grid, 11(2), 1702–1713. https://doi.org/10.1109/TSG.2019.2942581