Environmental Design Commons^™

A Framework To Predict Variability Characteristics In Building Load Profiles, Sam Moayedi, Andrew Parker, Kevin James, Xiaoyue Cheng, Michael Hempel, Hamid Sharif, Mahmoud A. Alahmad

Durham School of Architectural Engineering and Construction: Faculty Publications

The expansion of Advanced Metering Infrastructure (AMI) has provided building operators and researchers detailed information on building energy consumption. The majority of AMI systems, however, record data at relatively low resolutions of 15, 30, or 60 minutes, due to cost, storage and bandwidth limitations. Emerging applications in power flow analysis, Quasi-Static Time-Series Simulation (QSTS), smart grid integration and load matching, however, require data at higher resolutions. Short-term energy demand can deviate significantly from long-term averages, with an unknown magnitude and frequency when only low-resolution load profile data is available. This paper presents a novel data-driven approach to predict characteristics of …