The goal of this project is to develop an high spatial and temporal resolution electricity demand model for South Carolina. This model will be built 'bottom-up' using load profile models of residential, commercial, and industrial customers available from the Department of Energy
The first step in this process is to identify buildings throughout the state from remote sensing data (imagery and LiDAR) using machine learning, image classification and feature recognition. These building footprints will be combined with information from esri's Business Analyst dataset to identify business type. These analyses will be run with help from Clemson Center for Geospatial Technologies through Clemson's Condor system to reduce the time requirements.
Once developed, the model will be able to predict patterns in peak and average load based on regional population and economic development projections. This effort feeds into the Energize! project and will also assist in integrated resource planning by electric utilities, as well as the development of future South Carolina State Energy Plans. Future work will expand to other energy resources (such as transportation fuels), and look to couple the energy model with food and water systems to explore the food-energy-water nexus for the state.