Data and Tools

NREL's computational applications—data, tools, and software—drive advancements across energy efficiency, sustainable transportation, renewable power technologies, and the knowledge base to optimize energy systems.

Our applications aim to solve models of behavior and control of energy carriers. Technologies incorporate material and chemistry theory, inverse design, development of digital twins for mobility, and network systems understanding and control.

Below is a selected list of computational applications. Browse all NREL's data and tools.

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting

BuildingsBench platform enables researchers studying time series foundation models to benchmark their methods on a challenging load forecasting problem.

BUTTER: An Empirical Deep Learning Experimental Framework

The framework enables researchers to run high volumes of computational experiments, including machine learning experiments, in a highly distributed asynchronous way.

ExaWind Software Suite

NREL provides an open-source suite of codes that simulate wind turbines and wind farms.

Pele Software Suite

The software suite simulates and maps how fuel properties affect turbine performance.

Questaal Software Suite

The software suite of electronic structure programs answers condensed matter theory questions about solid-state structures.