Design of Future Energy Infrastructure: Understanding trade-offs between Renewable Capacity, Storage and Transmission Networks for Low-Carbon Landscape

Abstract

In 2021, the United States committed to achieving net-zero greenhouse gas emissions by 2050, requiring a fundamental transformation of its energy infrastructure. This thesis develops a nationwide optimization model to minimize capital expenditures and understand the trade-off between renewable capacity, storage, and transmission networks. The results show that the least-cost configuration, achieved when nuclear and battery capital costs fall by 50%, requires approximately $3.25 trillion in new investment - a 37% reduction relative to the baseline scenario. Comparative scenario analysis reveals a marked shift toward centralized storage when nuclear costs decline, which improves reliability and reduces contingency requirements - mirroring inventory pooling dynamics in supply chains. Concurrently, wind capacity additions fall sharply, with each 10% reduction in nuclear cost halving the predicted wind capacity addition. Transmission infrastructure evolves accordingly: 765 kV lines decline as nuclear becomes more decentralized, while 230 kV lines expand modestly to manage increased intermittency. By quantifying trade-offs across technologies and identifying system tipping points, this work offers a framework for policymakers and long-horizon investors.