Authors: Jeff Friesen*, Radiant Labs, Adam Stenftenagel, Radiant Labs
Topics: Energy, Sustainability Science, Environment
Keywords: climate change, interactive visualizations, renewable energy
Session Type: Paper
Start / End Time: 11:10 AM / 12:25 PM
Room: Grand Ballroom 2, Sheraton, IM Pei Tower, Second Floor Level
Presentation File: No File Uploaded
To rapidly decarbonize a city's infrastructure and transform its land to be a carbon sink instead of carbon source, thousands of costly decisions need to be made by residents, business owners and city planners. Thousands of sales need to be made by building contractors, vehicle dealers and farmers. For the US, it's hundreds of millions of decisions and sales. For the world, it's billions. For real transformation, cost-effective options need to be available to decision makers.
We're building a global, cost-benefit optimization platform, at the resolutions needed by decision makers.
Traditional methods of working with this much data typically involve pre-aggregation and loss of resolution. But you can't, for example, build a value proposition for a homeowner by giving them neighborhood averages of upgrade costs and savings. Spatially-aware interactions with large data sets are allowing us to approach problems in completely new ways.
I'll demo our product currently used by cities:
* Interact with every building in a city - which includes NREL's ResStock energy modeling and NREL's rooftop solar potential data. This allows us, for example, to identify the buildings in a city that are good candidates for net-zero retrofits
* Effectively visualize 2 million scenarios of building upgrades, given different market conditions using a combination of machine learning and massive compute resources.
Our current technology can scale to ~500K data points. I'll also briefly discuss the next stage of our development, which will allow us to interact with billions of spatially-aware data points.