Much of the world is aiming for net-zero emission targets, but hydrocarbon fuels are very well-suited for many applications. Liquid electrofuels, derived from renewable hydrogen and carbon dioxide captured from the atmosphere, could be a good option for aviation and other difficult-to-electrify sectors. Electrofuels are directly compatible with existing infrastructure, but they are currently expensive, and it is not immediately clear where we should focus research, development, and deployment efforts to most effectively bring down these costs.
Stanford postdoc Evan D. Sherwin’s latest paper, “Electrofuel Synthesis from Variable Renewable Electricity: An Optimization-Based Techno-Economic Analysis,” combines optimization and techno-economic analysis, which estimates the cost of emerging technologies, to gain insight into the future cost of electrofuels using carbon dioxide removed from the atmosphere using direct air capture (DAC) and powered primarily by solar or wind electricity. In particular, this optimization-based approach provides insights into which factors (e.g. the efficiency or cost of a given component) are most important for future cost reductions, accounting for possible changes in system operation as the facility attempts to economically operate expensive equipment using variable renewable electricity.
The paper finds that although electrofuels produced today would be expensive, costs could approach parity with fossil jet fuel by 2050. The first priority for achieving this is reducing the capital cost of DAC, electrolyzers, and renewable electricity, but improving system flexibility is of comparable importance. Flexibility can come in many forms, including storage of electricity, heat, hydrogen, and carbon dioxide, as well as faster ramping or lower minimum operating levels for individual components, or net-zero interconnections to the electric or natural gas grid (offset by DAC with sequestration at another location). This optimization-based approach allows direct assessment of the value of flexibility, which is otherwise difficult to estimate.
This work highlights optimization as a tool to explore the dynamics of possible futures that may look very different than our own, informing the research, development, and deployment investments we make now to help chart a course for the world we want.