The goal of this project is to develop and apply signal processing, feature extraction, filtering, dynamic Bayesian and Time Series methods, to reduce the commissioning costs of buildings by discovering energy inefficiencies imprinted in “Smart Meters” deployed throughout the building. The analysis initially focuses on data from dozens of buildings on the UC campuses and will leverage “natural experiments” in which commissioning agents have documented and corrected energy waste while logging pre- and post-project energy consumption data. The findings will be presented to policy makers and energy companies to obtain more data and additional funding. This multi-disciplinary project brings together students at UC Berkeley and UC Santa Cruz from Energy and Resources, Building Science, Engineering, Technology and Information Management, and Analytics.
As the U.S. continues in its shift from a manufacturing to a services oriented economy, engineering education must respond.
The Residential Load Monitoring Project aims to improve energy consumers’ knowledge of their consumption by…
In electricity grids, demand response (DR) changes the traditional way that customers consume electricity.