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Machen, Scott

Publications and source records attributed to Machen, Scott.

Quantifying the challenge of reaching a 100% renewable energy power system for the United States

We simulate pathways for achieving up to 100% renewable energy (RE) electric power systems for the contiguous United States. Under base conditions, the least-cost buildout has RE penetration growing up to 57% in 2050. Relative to this base scenario, average CO2 abatement costs of achieving 80%, 90%, 95%, and 100% RE are $25, $33, $40, and $61/ton, respectively, with system costs growing from $30 to $36/MWh at 95% (achieved in 2040) and $39/MWh at 100%. Incremental abatement costs from 99% to 100% RE reach $930/ton, driven primarily by the need for firm RE capacity. In addition to the base conditions, we also examined 22 alternative conditions for a buildout of up to 100%. These sensitivities capture different technology trajectories, compliance requirements, requirement timing, electrification, and transmission availability. Nonlinear marginal costs for the last few percent approaching 100% RE were found for all sensitivities, which might motivate alternative nonelectric-sector abatement opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Regional Energy Deployment System (ReEDS) Model Documentation (Version 2020)

The Regional Energy Deployment System (ReEDS) model is a capacity expansion and dispatch model that is primarily used for the contiguous U.S. electric power sector. The model relies on system-wide least cost optimization to estimate the type and location of future generation and transmission capacity. This document describes details of how the model is formulated, how it functions, and many of the key inputs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Storage Futures Study: Economic Potential of Diurnal Storage in the U.S. Power Sector

We model the evolution of the U.S. electricity sector from 2020 through 2050 and find significant market potential (>125 GW) for diurnal energy storage across all 19 scenarios considered. Most of this storage has 4-6 hours of duration. We find that storage deployment is driven primarily by the combination of capacity value and energy time-shifting value, and that the combination of these value streams is needed for optimal storage deployment to be realized. We also find a strong correlation of PV penetration and storage market potential. Cost and performance metrics in this study focus on Li-ion batteries because the technology has more market maturity than other emerging technologies but results from this study can be generalized to any technologies that meet the cost and performance projections assumed.

25 ENERGY STORAGE↗