(421a) Economic Optimization of Grid-Integrated Clean Hydrogen and Ammonia Production

Using electricity generated from renewable sources to produce hydrogen via water electrolysis has been a ubiquitous topic in recent academic research, industrial development, and policy discussion. This electrified hydrogen production can lower the carbon intensity of industries which traditionally source hydrogen from methane or other fossil fuels. Perhaps more impactfully, renewable hydrogen offers vast possibilities as a carbon neutral energy storage medium or transportation fuel. Further converting this hydrogen to ammonia by combining it with air-derived nitrogen serves to increase its energy density and thus lower its storage cost in energy or transportation applications. Renewable ammonia can also be used as a sustainable nitrogen fertilizer; today, ammonia production consumes up to 50% of hydrogen produced from fossil fuels [1].

Renewable electrification of hydrogen and ammonia production has transformational potential. At present, however, this paradigm is still cost prohibitive relative to the conventional approach of using fossil fuels as the hydrogen source [2-5]. Coupling electrified chemical production with the grid is a potential approach to overcome this. As grid systems undergo a transition to include higher (and eventually dominant) fractions of renewables in their generation mix, they experience increased congestion and curtailment [6]. Time-varying chemical production as controllable load can serve to alleviate this congestion while also allowing otherwise curtailed energy to be monetized. From the chemical producer’s perspective, interacting with the grid in this manner can provide low-cost or even negative-cost energy. Exploiting these potential synergies between the grid and electrified chemical producers can help drive near-term economic viability.

In this work, we optimize the economics of grid-integrated hydrogen and ammonia production. Specifically, we consider cases of (i) electrolysis-based hydrogen production and (ii) subsequent ammonia synthesis by a Minnesota transmission-scale power generation entity with natural gas, nuclear, wind, and solar generation assets. We develop a combined capacity planning and dispatch optimization model to minimize overall system costs by selecting and sizing chemical production technologies from a set of technical alternatives, for example, alkaline vs. PEM vs. solid oxide electrolysis for hydrogen production. The model simultaneously optimizes the dispatch of existing power generation assets within each of their technical (e.g., ramping, minimum up and down times) and regulatory constraints (e.g., minimum renewable generation thresholds) while also scheduling the operation of newly installed chemical production. Considering dispatch at the capacity planning stage gives rise to the above-described advantages of coupling grid operations and electrified chemical production, while the use of optimization maximizes the benefit of such integration [7].

We perform case studies for hydrogen and ammonia end products across a range of chemical production scales. We perform this analysis for present-day through 2035, considering the expected increase of renewables in the generation mix and decrease in chemical production technology costs, primarily electrolysis. For each case study, we compute the carbon intensity of the produced hydrogen or ammonia to identify trade-offs between chemical production cost and emissions in this new chemical production paradigm. Further, we consider scenarios where fossil-fueled generation assets can be retrofitted to enable hydrogen or ammonia fueling in an aim to reduce the emissions intensity of the energy supply sector. Overall, the goal of this work is to determine the viability of this grid-coupled chemical production as a path forward for near-term decarbonization of both the chemical manufacturing and energy industries.

References

[1] Lan, R., & Tao, S. (2014). Frontiers in Energy Research 2, 35.

[2] Mallapragada, D. S., Gençer, E., Insinger, P., Keith, D. W., & O’Sullivan, F. M. (2020). Cell Reports Physical Science 1(9), 100174.

[3] Armijo, J., & Philibert, C. (2020). International Journal of Hydrogen Energy 45(3), 1541-1558.

[4] Nayak-Luke, R., Bañares-Alcántara, R., & Wilkinson, I. (2018). Industrial & Engineering Chemistry Research 57(43), 14607-14616.

[5] Fasihi, M., Weiss, R., Savolainen, J., & Breyer, C. (2021). Applied Energy 294, 116170.

[6] Schermeyer, H., Vergara, C., & Fichtner, W. (2018). Energy Policy, 112, 427-436.

[7] Palys, M.J. & Daoutidis, P. (2020). Computers and Chemical Engineering 136, 106785.