The Role for Electricity Transmission in Net-Zero Energy Systems: A Spatially Resolved Analysis of the Continental US

Due to climate change and the need for rapid emission reduction, new technologies including, hydrogen and negative emission technologies (NETs) including direct air capture and bioenergy with carbon capture and sequestration (BECCS) are being developed for integration into energy systems. Additionally, variable renewable energy (VRE) resources, which are expected to play a major role in decarbonization pathways, exhibit significant spatial variability and reliance on transmission infrastructure compared to existing fossil-fuel based energy systems, placing greater emphasis on transport and storage of material and energy. This case study evaluates pathways to a net-zero energy system in the continental US. To inform spatial infrastructure outcomes, we use an open-source energy system model that explores decarbonization pathways for the broader energy system under various technology availability and transmission network expansion assumptions. To attain a deeper understanding of technology interactions in a net-zero energy system, we use the Modeling to Generate Alternatives formulation that generates near-optimal solutions within a pre-defined threshold of the cost-optimal solution. We find that transmission network expansion enables the increased usage of high-quality wind resources. When the power sector is coupled with the hydrogen supply chain, the use of electrolyzers increase demand for electricity from VRE resources further. NETs, specifically BECCS, allow for the inclusion of natural gas in the generation mix while adhering to net-zero emissions targets. This approach helps mitigate the need for extensive transmission network expansion and VRE resources. We identify several transmission paths that policymakers should prioritize for expansion. Our analysis of near cost-optimal solutions provide confidence in the cost-optimal technology dependencies we identified.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Institute for Data, Systems, and Society

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Shi, Nicole Xiaoyang

Advisor dc:contributor.advisor

• Mallapragada, Dharik

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/151926

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151926