Electricity Disaggregation

In this project we focus on a specific class of unsupervised algorithms based on deep learning techniques that can learn instantaneous power waveforms for individual devices as well as their activation patterns given sufficient data from a single meter.

Estimating Climate Change Impacts on Water and Electric Power Infrastructure in the Southeast U.S.

In this project we focus on estimating the effects of climate change on electric power systems.

GridBallast: Autonomous Load Control For Grid Resilience

The GridBallast project will create low-cost demand-side management technology to address resiliency and stability concerns accompanying the growth of distributed energy resources.

Understanding Electricity Demand Patterns Coupled With On-Site Solar Generation

In this project we study the potential of existing datasets to provide information necessary for decision-making in different contexts: from solar home systems for low-income rural residents in Africa, to utility net-metering datasets from United States households.