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Several roadmaps and international projects are interested in the development of the hydrogen economy for the transportation system. Yet, the development of a hydrogen economy suffers from a lack of infrastructure to store and supply H2 fuel to the refuelling stations, while at the same time, hydrogen can be just seen as one alternative among others to compete with the current fossil fuels. To determine if hydrogen is a competitive option, many scenarios must be assessed considering not only the cost as the target to determine the feasibility but, also environmental and safety objectives. This work is focused on the design of a hydrogen supply chain for deployment scenarios in the Midi-Pyrénées region in France based on multi-objective optimization. Specific constraints related to the energy sources have been integrated and a multi-period long-term problem is examined (2020-2050). Two solution strategies will be implemented to solve this multi-period problem: a global optimization through e-constraint method and a sequential optimization through lexicographic and e-constraint methods. The consideration of different geographical scales and the impact of the initiation step in the development of a sustainable supply chain have been highlighted. [ABSTRACT FROM AUTHOR]

Abstract: This work considers the potential future use of hydrogen in fuel cell electrical vehicles to face problems such as global warming, air pollution, energy security and competitiveness. The lack of current infrastructure has been identified as one of the main barriers to develop the hydrogen economy. This work is focused on the design of a hydrogen supply chain through mixed integer linear programming used to find the best solutions for a multi-objective optimization problem in which three objectives are involved, i.e., cost, global warming potential and safety risk. This problem is solved by implementing an ɛ-constraint method. The solution consists of a Pareto front, corresponding to different design strategies in the associated variable space. Multiple choice decision making is then recommended to find the best solution through an M-TOPSIS analysis. The model is applied to the Great Britain case study previously treated in the dedicated literature. Mono and multicriteria optimizations exhibit some differences concerning the degree of centralization of the network and the selection of the production technology type. [Copyright &y& Elsevier]