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OR-SAGE Framework for Siting Supercritical CO2 Reactors

OR-SAGE Framework for Siting Supercritical CO2 Reactors
Overview of OR-SAGE tool process

OR-SAGE (Oak Ridge Siting Analysis for power Generation Expansion) can be used to identify sites where a prototype chemical reactor would be the best options with respect to different technology scenarios. Specifically, OR-SAGE will help to identify the ideal site selection for maximizing the benefits of conversion of super critical CO2 to methanol, carbon monoxide, or small hydrocarbons.
 

  • OR-SAGE is a computational framework that allows for mapping, querying, modeling, and decision analysis of study areas. The spatial output can be structured to be visual, allowing for easier analysis of location data. 
  • The OR-SAGE tool uses industry-accepted practices and array of data sources to identify suitable areas for siting new power plant sites or evaluating existing power plant locations for repowering with clean energy technologies. The OR-SAGE siting process can be easily adapted for siting industrial facilities.
     
OR-SAGE Framework for Siting Supercritical CO2 Reactors
Nominal, bounding SMR composite map detailing siting challenges
  • OR-SAGE capabilities have been integrated into various DOE’s tools including STAND (Siting Tool for Advanced Nuclear Deployment) and ARPA-E’s ANSL (Advanced Nuclear Siting Locator) tool. Other applications include the evaluating the potential of repowering retired and existing coal power plants with nuclear energy. 
  • The OR-SAGE technology is unique to ORNL; thus, this team is uniquely positioned to enhance the overarching goal of establishing a proof-of-concept CO2 conversion reactor based on scCO2 with decision analysis capability.
  • As part of ORNL’s FY23 DecisionScience@ORNL Analysis Projects, “The selection committee recognizes the merits of your ideas and methodologies, the feasibility of delivering results, and the project’s potential to attract follow-on funding.”
     

Contributors: Femi Omitaomu, CSED/CCSD, Randall J. Belles, NEFCD/FFESD, Brandon Miller, CSED/CCSD, Michael D. Muhlheim, NEFCD/FFESD 

Sponsor: FY23 DecisionScience@ORNL Analysis Projects