Abstract
Advanced technologies utilising renewable energies have been advanced rapidly to achieve the Net Zero target, leading to significant cost reduction. However, the intermittency of renewable energy results in unstable power supply, which could be mitigated through renewable energy storage. Ammonia stands out as a promising energy carrier, distinguished by its cost-effective transportation and storage, high energy density, well-established infrastructure, and versatile applications. In this work, we design a green ammonia production system including H2 generation by using proton electrolyte membrane (PEM) electrolysis, N2 recovered from off gas, and NH3 synthesis by using Haber-Bosch Process. An amine-based carbon capture is also integrated to further reduce carbon emissions and nitrogen enrichment. We then develop rigorous process models of reactive equipment to enhance the accuracy of process simulation. Sensitivity analysis is conducted to investigate effects of several key parameters on process performance and the optimal operating conditions are thus obtained to achieve maximum energy savings. The computational results demonstrate that the developed process models have good agreement in predictions with the experimental and plant data. The equivalent energy consumption for green ammonia production in our proposed system is 37.6 GJ t−1 NH3 with energy efficiency of 48.8 %. The techno-economic evaluation shows that the levelized cost of ammonia in our system is 1169 $ t−1 NH3, which is expected to be reduced to 410.5 $ t−1 NH3 in 2050 when the carbon tax of 130 $ t−1 CO2, electricity of 20 $ MWh−1 and 90 % reduction of the current capital cost (227 $ kW−1) in H2 subsystem are applied. This is aligned with the prediction by IRENA.
| Original language | English |
|---|---|
| Article number | 138068 |
| Journal | Energy |
| Volume | 336 |
| Early online date | 18 Aug 2025 |
| DOIs | |
| Publication status | Published - 1 Nov 2025 |
Keywords
- renewable energy storage
- green ammonia
- process design
- rigorous models
- techno-economic evaluation