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Where to build the ideal solar-powered ammonia plant? Design optimization of a Belgian and Moroccan power-to-ammonia plant for covering the Belgian demand under uncertainties

par Verleysen, Kevin ;Coppitters, Diederik;Parente, Alessandro ;Contino, Francesco
Référence Applications in Energy and Combustion Science, 14, 100141
Publication Publié, 2023-06

Article révisé par les pairs

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Résumé :

Regions with abundantly available renewable energy are not necessarily the same as those with a high population density and energy consumption. Therefore, renewable energy can be produced in optimal climate conditions with a remote renewable hub and transported to these population-dense regions. To establish this energy transport to these regions, ammonia provides a flexible, easy-to-handle energy carrier. However, current literature rarely considers the impact of techno-economic uncertainty on the feasibility of this transport. Using those uncertainties, we performed a robust design optimization on the levelized cost of ammonia and the power-to-ammonia efficiency to compare the local (Belgium) and remote (Morocco) ammonia production and transport to Belgium. This paper provides the robust designs (i.e. least sensitive to uncertainty) for local and remote renewable ammonia production and the advantages of both approaches on the levelized cost and energy efficiency. The results confirm that ammonia production in regions with high solar irradiance followed by the transport of ammonia is cost-effective and robust (601 euro/tonneNH3 in mean and 98 euro/tonneNH3 in standard deviation) over local production (852 euro/tonneNH3 in mean and 139 euro/tonneNH3 in standard deviation). However, local ammonia production provides for more efficient (54.8% in mean) and less sensitive power-to-ammonia plant designs (0.16% in standard deviation), while the production in Morocco is less efficient (52.2% in mean) and more sensitive to uncertainties (0.39% in standard deviation). The capacity of the photovoltaic arrays and the electrolyzers highly influences both objectives. The sensitivity analysis shows that capital and operational expenses of the photovoltaics and electrolyzer stack dominate the designs with the lowest levelized cost in mean and standard deviation. However, the energy consumption uncertainty of the Haber–Bosch also impacts the cost of the lowest mean levelized cost. This uncertainty also dominates the designs with the highest energy efficiency in mean and lowest standard deviation.