The use of optimization tools for the Hydrogen Circular Economy

Abstract: Hydrogen losses in industrial waste gas streams, estimated as 10 billion Nm3 per year in Europe, constitute potential sources for hydrogen recovery. Further use of this waste hydrogen in fuelled devices promotes a world powered by hydrogen while reinforcing the paradigm of the Circular Economy. This will require the availability of effective technologies for hydrogen recovery and purification as well as the techno-economic assessment of integrating the upcycled gas into a sustainable supply chain using decisionmaking tools. This work using a mixed-integer programming model (MILP), and scenario analyses, develops the techno-economic modelling over the 2020-2050 period, at a regional scale comprising the north of Spain. Two main industrial waste streams are considered; one produced at integrated steel mills and coke making industries and, the second one, at chlor-alkali plants. The proposed optimization model integrates the following items: i) technology selection and operation, ii) hydrogen demand forecast, iii) geographical information, iv) capital investment models, and v) economic models. The optimal solutions that arise from the combination of all the infrastructure elements into the mathematical formulation, define the gradual infrastructure investments over time that are required for the transition towards a sustainable future energy mix, including surplus hydrogen. The results confirm that the critical factor in the configuration of the proposed energy system is the availability of industrial surplus hydrogen, contrary to conventional hydrogen energy systems that are mainly controlled by hydrogen demand. Additionally, this study confirms that the optimal levelized cost of upcycled hydrogen is in the range of 0.35 to 1.09 €/kg H2, which is 1.5 to 2 times lower than the price of hydrogen obtained by steam conversion of natural gas.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Autoría: Yáñez M., Ortiz A., Brunaud B., Grossmann I., Ortiz I.,

 Fuente: Computer Aided Chemical Engineering, 2019, 46, 1777-1782

Editorial: Elsevier

 Año de publicación: 2019

Nº de páginas: 6

Tipo de publicación: Artículo de Revista

DOI: 10.1016/B978-0-12-818634-3.50297-6

ISSN: 1570-7946,2543-1331

Proyecto español: CTQ2015-66078-R

Url de la publicación: https://doi.org/10.1016/B978-0-12-818634-3.50297-6