Measuring the Energy Capital of the World

MEASURING THE ENERGY CAPITAL

I N D I V I D U A L S T U D E N T P R O J E C T

METHODS: DATA VISUALIZATION, PHOTOGRAMMETRY

TOOLS: PYTHON, BLENDER, GOOGLE EARTH

Measuring the Energy Capital of the World is a project that combines computational pattern analysis with building energy ratings to create dynamic visuals for understanding operational energy consumption. Using publicly available metrics, building performance was calculated through the UPC, with ratings derived from USEIA data on annual kWh consumption for commercial supertall structures. A 3D site model of Houston's skyline was photo-scanned into Blender using Google Earth satellite imagery. The visualization features a particle density simulation that highlights buildings with the highest operational energy (OE) usage within the Houston skyline cluster, offering a meta-analysis of the city's title as the "Energy Capital of the World."

S I M U L A T I O N

M E A S U R E M E N T S

To create this visual, two datasets were explored: Union Power Cooperative (UPC) and the US Energy Information Administration (EIA). The UPC is a nonprofit organization that provides metrics and calculations on a building’s energy performance. The data used in the calculations were publicly available metrics: age of the building, square footage, lighting type, hours of operation, refrigeration, heating and cooling type, and water system type. The USDE calculations were used to visualize the average annual particle system metrics, low: 0-499K kWh, med: 500-999K kWh, high 1M+ kWh. This data was gathered from the EIA listing of 16.9 per sqft. kWh used annually for administrative/professional buildings multiplied by the average sqft of supertall buildings in the US.

UPC building performance calculations after inputting publicly available metrics.

EIA dataset explored to create supertall building performance ratings.

Building performance ratings guide made as a reference to the simulation.

T H E S I T E

Based on the calculated annual kWh per selected supertall buildings, the particles were proportionally keyframed when dispersed from the starting point of the particle path flow. For example, One Shell Plaza has an annual 40 kWh, therefore, 400 particles were set to surround its location from the assigned data table. This served as a representation for the above average use of operational energy for this building cluster -- all in the red zone.