U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


CERF - A Geospatial Model for Assessing Future Electricity Capacity Expansion
Published: February 04, 2018
Posted: May 31, 2019

Model accounts for economic, environmental, and practical constraints to identify feasible power generation sites.

The Science
Credible projections of future changes in climate, energy, and related human and natural systems are dependent on realistic scenarios of future electricity system growth. However, electricity capacity expansion models typically do not account for water availability, interconnection costs, regulatory constraints, or other factors that may restrict power plant construction. A team from the U.S. Department of Energy’s Pacific Northwest National Laboratory used the Capacity Expansion Regional Feasibility (CERF) model to evaluate the potential for siting different energy production technologies over the contiguous United States at a resolution of 1 km2.

The Impact
By accounting for economic, environmental, and practical constraints that influence power plant siting, CERF will improve projections of future energy system growth and, ultimately, attendant changes in the integrated human-Earth system. Improved understanding of electricity capacity expansion constraints can also provide insight into factors that may influence long-term energy system resilience.

Summary
The open-source CERF model evaluates the feasibility of electricity capacity expansion plans by considering a wide range of factors that restrict power plant siting, including land use, environmental regulations, water availability, infrastructure access, and net operational costs. By combining this high-spatial-resolution information with larger-scale information about energy supply and demand from an integrated human-Earth system model such as GCAM, CERF can provide a comprehensive assessment of how many power plants of each type can be accommodated across a given region under a given scenario. Power plant siting is first evaluated based on geospatial suitability, which includes 32 base constraint layers and an additional seven layers of technology-specific constraints for 17 different power production technologies. The feasibility of the expansion plan is then further evaluated by considering economic factors such as the distance to existing transmission infrastructure, technology-specific marginal operating costs, and technology- and location-specific marginal energy values. Finally, an economic optimization algorithm is used to assign power plants to each 1 km2 grid cell. CERF thus provides a holistic, multi-sector, multi-scale assessment of the on-the-ground feasibility of a given electricity capacity expansion scenario. This information can be used to evaluate and refine projections of future energy system growth, which is a key factor driving future Earth system changes.

Contacts (BER PM)
Bob Vallario
Multi-Sector Dynamics
Bob.Vallario@science.doe.gov

(PI Contact)
Ian Kraucunas
Pacific Northwest National Laboratory
Ian.Kraucunas@pnnl.gov

Funding
The original development of the CERF model was conducted under the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory, a multi-program national laboratory operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Further development and ongoing demonstration of CERF is supported by the U.S. Department of Energy, Office of Science, as part of research in the Multi-Sector Dynamics, Earth and Environmental System Modeling Program.

Publication
Vernon CR, N Zuljevic, JS Rice, TE Seiple, MCW Kintner-Meyer, N Voisin, IP Kraucunas, C Jin, J Olson, L Schmidt, SL Morris, and P Patel. “CERF - A Geospatial Model for Assessing Future Energy Production Technology Expansion Feasibility.” Journal of Open Research Software 6(1), art. 20 (2018). [DOI: 10.5334/jors.227]

Related Links
https://github.com/IMMM-SFA/cerf

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Multisector Dynamics (formerly Integrated Assessment)

Division: SC-23 BER

 

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