Optimal Operation of a Novel Small-Scale Power-to-Ammonia Cycle under Possible Disturbances and Fluctuations in Electricity Prices
Pascal Koschwitz,
Chiara Anfosso,
Rafael Eduardo Guedéz Mata,
Daria Bellotti,
Leon Roß,
José Angel García,
Jochen Ströhle,
Bernd Epple
Affiliations
Pascal Koschwitz
Department of Mechanical Engineering, Institute for Energy Systems and Technology, Technical University of Darmstadt, Otto-Berndt-Str. 2, 64287 Darmstadt, Germany
Chiara Anfosso
Thermochemical Power Group, Dipartimento di Macchine Sistemi Energetici e Trasporti, University of Genova, Via Montallegro 1, 16145 Genova, Italy
Rafael Eduardo Guedéz Mata
Department of Energy Technology, School of Industrial Engineering and Management, KTH Royal Institute of Technology, Brinellvägen 68, 10044 Stockholm, Sweden
Daria Bellotti
Thermochemical Power Group, Dipartimento di Macchine Sistemi Energetici e Trasporti, University of Genova, Via Montallegro 1, 16145 Genova, Italy
Leon Roß
Department of Mechanical Engineering, Institute for Energy Systems and Technology, Technical University of Darmstadt, Otto-Berndt-Str. 2, 64287 Darmstadt, Germany
José Angel García
Department of Energy Technology, School of Industrial Engineering and Management, KTH Royal Institute of Technology, Brinellvägen 68, 10044 Stockholm, Sweden
Jochen Ströhle
Department of Mechanical Engineering, Institute for Energy Systems and Technology, Technical University of Darmstadt, Otto-Berndt-Str. 2, 64287 Darmstadt, Germany
Bernd Epple
Department of Mechanical Engineering, Institute for Energy Systems and Technology, Technical University of Darmstadt, Otto-Berndt-Str. 2, 64287 Darmstadt, Germany
Power-to-Ammonia (P2A) is a promising technology that can provide a low-emission energy carrier for long-term storage. This study presents an optimization approach to a novel small-scale containerized P2A concept commissioned in 2024. A dynamic nonlinear optimization problem of the P2A concept is set up, employing the non-commercial MOSAIC® software V3.0.1 in combination with the NEOS® server. In total, seven optimization solvers, ANTIGONE®, CONOPT®, IPOPT®, KNITRO®, MINOS®, PATHNLP®, and SNOPT®, are used. The first and main part of this work optimizes several disturbance scenarios of the concept and aims to determine the optimal reactor temperature profile to counter the disturbances. The optimization results suggest, for example, lowering the reactor temperature profile if the hydrogen and nitrogen inlet streams into the system decrease. The second part of this work presents a crude dynamic optimal scheduling model. This part aims to determine the amount of ammonia to be produced and sold given a randomized price of electricity for three consecutive points in time. The optimization results recommend decreasing production when the price of electricity is high and vice versa. However, the dynamic model must be improved to include fluctuations in the price of ammonia. Then, it can be used as a real-time optimization tool.
