Transforming Energy through Computational Science: Computing for Clean Energy

Research output: NRELFact Sheet


This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.
Original languageAmerican English
Number of pages4
StatePublished - 2021

NREL Publication Number

  • NREL/FS-2C00-79695


  • advanced computing
  • artificial intelligence
  • Biden
  • carbon-free
  • clean energy
  • climate
  • cloud computing
  • computational materials and chemistry
  • computational science
  • continuum mechanics
  • data analytics
  • datacenter
  • decarbonization
  • demonstration
  • deployment
  • digital twins
  • Eagle
  • energy systems
  • Energy Systems Integration Facility
  • environmental justice
  • experimentation
  • forecasting
  • grid
  • high-performance computing
  • innovation
  • Insight Center
  • investment
  • machine learning
  • modeling
  • renewable energy
  • research and development
  • scalability
  • simulation
  • supercomputer
  • technology
  • transportation
  • visualization


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