Regional Integrated Assessment Modeling: Assessing Opportunities and Vulnerabilities in a Rapidly Evolving U.S. Natural Gas Industry Principal Investigators:

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Regional Integrated Assessment Modeling: Assessing Opportunities and Vulnerabilities in a Rapidly Evolving U.S. Natural Gas Industry Principal Investigators: Thomas J. Wilbanks (ORNL), Ian P. Kraucunas (PNNL), Steven J., Fernandez, (ORNL), Leon E Clarke (PNNL), Olufemi A. Omitaomu, (ORNL) Pralit L Patel (PNNL), Melissa R. Allen (ORNL), Son H. Kim (PNNL), James J. Dooley (PNNL) Researchers at PNNL and ORNL are developing a framework which is loosely coupling GCAM-USA and Connected Infrastructure Dynamic Models (CIDM) to anticipate opportunities from enhanced domestic natural gas production as well as emerging infrastructure vulnerabilities. Assessing the natural gas system in light of drivers such as a changing climate, changing consumption patterns and changing production locations provided an illustrative example of the framework’s feasibility. This technological revolution is driving significant changes in natural gas consumption across different sectors of the economy and across states and regions within the US. GCAM-USA GCAM-USA includes detailed US state- level scale data housed within a fully global energy and agriculture model Integrated Assessment Model. Within this framework, modeled shifts in the US domestic energy system included the final demand sectors and electricity and refined liquids production over the century across technology, policy and economic scenarios. Going forward, we will explore how drivers of major changes in the US energy system would positively or negatively impact the resilience of the US natural gas system. Examples of key drivers include: CIDM CIDM is a suite of tools for modeling and analysis of connected infrastructures and their vulnerabilities. CIDM has been used in this research to: (1) downscale energy consumption data at state/regional scale to neighborhood (at approximately 1km x 1km) or county scale (2) identify suitable land/area/zone for siting new energy infrastructure using industry accepted siting criteria and modeling approaches, and (3) placement of infrastructure nodes with respect to node requirements for evaluating policy scenarios. Future climate and energy policy will play a large role in shaping how the US energy system evolves. Changes in the number of US cooling degree days (CDD) will drive major changes in US energy system. Altered water availability could be a major driver of changes in the US energy system. Existing natural gas pipelines and storage facilities Available areas for future natural gas pipelines and storage facilities By overlaying these potential routings with CIDM assessments of the pipeline vulnerable nodes new scenarios for the Pennsylvania-New York regions, Canadian import-export regions, and Southeast- Gulf Coast flow reversals were illustrated. Use of the coupled framework was feasible. Conclusion : Early results suggest new pipeline and storage demands Projected natural gas Customer Distribution mid- century. Case Study Framework Motivation New large-scale production of previously uneconomic domestic natural gas resources contained in shale and other tight formations require anticipation of infrastructure scale vulnerabilities. Projected natural gas demand at mid-century. Projected natural gas suitable nodes at mid-century GCAM State Level Natural Gas Demand 2100 by Sector Forecast population movements resolved to 10 million neighborhood cells OR-Sage used to identify newly needed pipeline growth Storage sites to connect new sources of supply to new sources of consumption and identify vulnerable nodes compared to existing pipelines OR-Sage framework to identify siting options Create ensemble of demand maps under varying assumptions and policy options Allocate GCAM demand to the 10 million neighborhood Cells GCAM a fully coupled energy, agriculture, economic integrated assessment model for exploring alternate future scenarios. Most likely routes given new supply areas and demand flows could be estimated