Salgi, Georges Donslund, Bjarne Alberg Østergaard, Poul
Abstract
Hydrogen is an energy carrier that can potentially be used for introducing renewably generated electricity into the transportation sector. This paper presents a methodology for an overall energy system analysis of a hydrogen infrastructure, which meets a transportation hydrogen demand profile. The methodology starts by building a mathematical model for optimizing the economic operation of electrolyzers on the electricity market by use of Genetic Algorithms. Demand profiles from the optimization are then included in an overall energy system analysis model studying the electricity market and power balance system effects. A sample 2030 scenario analysis of Western Denmark is presented to demonstrate the applicability of the devised methodology. It is shown that Genetic Algorithms is a flexible tool that can be adapted to optimization problems involving energy storage. On the other hand, it is found that the ability of Genetic Algorithms to find a solution is highly dependent on initial variables and the storage constraint. Further analysis is required in order to test and expand the methodology and scenario results.
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