arXiv subjects

Michael J. Roberts

Publications and source records attributed to Michael J. Roberts.

3 recordsLinked to original sources

arXiv2026

Optimal transmission expansion modestly reduces decarbonization costs of U.S. electricity

Major government studies and policy reports project that substantial expansion of interregional transmission will be needed to integrate clean energy and ensure reliability in decarbonized power systems. Using the open-source Switch capacity expansion model with detailed representation of existing U.S. generation and transmission infrastructure, solar, wind, and storage resources, and hourly operations, we evaluate the role of interregional transmission across least-cost, carbon-priced, and zero-emissions scenarios for 2050. An optimal nationwide plan would more than triple interregional transmission capacity, yet this reduces the cost of a zero emissions system by only 7% relative to relying on existing interregional transmission, as storage, solar and wind siting, and nuclear generation serve as close substitutes. Regional cost and rent effects vary, with transmission generally favoring wind and hydrogen resources over solar and batteries. Sensitivity analysis shows diminishing returns: one-fifth of the benefits of full expansion can be achieved with one-twelfth of the added capacity, while cost reductions for batteries and hydrogen provide comparable or greater system savings than interregional transmission. Upgrading existing interregional corridors with advanced conductors roughly doubling capacity per link at half the cost of new builds reduces system costs by only 1.6%, suggesting that reconductoring benefits are modest and that realizing their full potential likely requires pairing with new connections on key corridors or complementary reductions in battery costs. These results suggest that while substantial transmission expansion is economically justified, a diverse set of flexibility resources can substitute for large-scale grid build out, and the relative value of transmission is highly contingent on technological and cost developments.

econ.GN↗

arXiv2025

Process and Policy Insights from an Intercomparison of Open Electricity System Capacity Expansion Models

This study performs a detailed intercomparison of four open-source electricity capacity expansion models - Temoa, Switch, GenX, and USENSYS - to evaluate 1) how closely the results of these models align when inputs and configurations are harmonized, and 2) the degree to which varying model configurations affect outputs. We harmonize the inputs to each model using PowerGenome and use clearly defined scenarios (policy conditions) and configurations (model setup choices). This allows us to isolate how differences in model structure affect policy outcomes and investment decisions. Our framework allows each model to be tested on identical assumptions for policy, technology costs, and operational constraints, allowing us to focus on differences that arise from inherent model structures. Key findings highlight that, when harmonized, models produce very similar capacity portfolios under current policies and net-zero scenarios, with less than 1% difference in system costs for most configurations. This agreement among models allows us to focus on how configuration choices affect model results. For instance, configurations with unit commitment constraints or economic retirement yield different investments and system costs compared to simpler configurations. Our findings underscore the importance of aligning input data and transparently defining scenarios and configurations to provide robust policy insights.

econ.GN↗

arXiv2022

Using Temperature Sensitivity to Estimate Shiftable Electricity Demand: Implications for power system investments and climate change

Growth of intermittent renewable energy and climate change make it increasingly difficult to manage electricity demand variability. Centralized storage can help but is costly. An alternative is to shift demand. Cooling and heating demands are substantial and can be economically shifted using thermal storage. To estimate what thermal storage, employed at scale, might do to reshape electricity loads, we pair fine-scale weather data with hourly electricity use to estimate the share of temperature-sensitive demand across 31 regions that span the continental United States. We then show how much variability can be reduced by shifting temperature-sensitive loads, with and without improved transmission between regions. We find that approximately three quarters of within-day, within-region demand variability can be eliminated by shifting just half of temperature-sensitive demand. The variability-reducing benefits of shifting temperature-sensitive demand complement those gained from improved interregional transmission, and greatly mitigate the challenge of serving higher peaks under climate change.

eess.SY↗