Abstract
Hydrogen has garnered significant research interest in the recent years as an alternative to carbon intense hydrocarbon technology pathways. The stated advantages of hydrogen include high energy density, low emissions at the point of consumption, and availability of diverse feedstock given the presence of the hydrogen atom in water, biomass, and fossil fuels. Nonetheless, emissions resulting from production, the generation of energy required for production, infrastructural material sourcing, and high costs of implementation have challenged the perception of hydrogen as a low carbon solution. The potential for sustainable production, and an existing infrastructural footprint directs attention to the role of ammonia and methanol as dense energy carriers (DECs) in future energy systems. Given the large degree of interaction among the constituent components in energy systems, it is possible to identify network configurations which are net-carbon neutral. To this end, multiscale approaches have become a mainstay in the design and analysis of energy transition scenarios. In the presented work, we discuss both the role of hydrogen as an energy vector in future energy economies, as also multiscale mixed integer programming (MIP) approaches, and data-driven predictive frameworks to model and optimize future hydrogen networks.
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Kakodkar, R., Sundar, S., Pistikopoulos, E.N. (2023). Hydrogen-Based Dense Energy Carriers in Energy Transition Solutions. In: Fathi, M., Zio, E., Pardalos, P.M. (eds) Handbook of Smart Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-97940-9_171
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