Abstract
Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber-Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber-Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process scales with a 0.77 capacity exponent, and at production scales below 6075 kg/h, it is less expensive than the conventional Haber-Bosch process.
Original language | English (US) |
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Article number | 91 |
Journal | Processes |
Volume | 6 |
Issue number | 7 |
DOIs | |
State | Published - Jul 1 2018 |
Bibliographical note
Funding Information:Funding: The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000804. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
Funding Information:
The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000804. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof
Publisher Copyright:
© 2018 by the authors.
Keywords
- Ammonia synthesis
- Design optimization
- Dynamic modeling