Dynamic Energy Mapping with 4D Community Energy Demand Visualization
Track: 3D GIS
Authors: yujie xu, Nina Baird
We describe the implementation, workflow, outcome and anticipated future development of a dynamic energy map as defined by Baird et al. in 2015. We used DOE commercial benchmark models to represent the heating and cooling energy demand of a conceptual community model, and built a visualization with CityEngine and Python. This 4D map reveals the variability in energy demand between buildings and across time, and displays patterns in individual and aggregate peak demand on several time scales.