Multiobjective and social cost-benefit optimisation for a sustainable hydrogen supply chain: Application to Hungary.

• New multiobjective optimisation model to design a sustainable hydrogen supply chain. • Optimisation of LCOH, GWP and safety risk and social cost-benefit. • Methodology applied to the "Green H 2 in Hungary" project. • H 2 demand for industrial and mobility markets (trucks and buses). • Comparison of single- and multiobjective optimisation strategies. This article presents a comprehensive approach to design hydrogen supply chains (HSCs) targeting industrial and mobility markets. Even if the inclusion of sustainability criteria is paramount, only a few studies simultaneously consider economic, environmental, and social aspects - the most difficult to measure. In this paper, the safety risk and the social cost-benefit (SCB) have been identified as quantifiable social criteria that would affect society and the end-users. The objectives of this research are (1) to design a sustainable HSC by using four objective functions, i.e., levelized cost of hydrogen, global warming potential, safety risk and social cost-benefit through a mixed-integer linear programming model; (2) to compare results from SCB and multiobjective optimisation. The integration of the SCB criterion at the optimisation stage is not a trivial task and is one of the main contributions of this work. It implies the minimisation of the total cost of ownership (TCO) for buses and trucks. The evolution of the HSC from 2030 to 2050 is studied through a multiobjective and multiperiod optimisation framework using the ε-constraint method. The methodology has been applied to a case study for Hungary with several scenarios to test the sensitivity of demand type and volume as well as the production technology. The results analysis highlights that (1) it is beneficial to have mixed demand (industry and mobility) and a gradual introduction/migration to electrolysis technology and fuel cell vehicles (FCVs) for a smooth transition. Liquid hydrogen produced via water electrolysis powered by nuclear and wind energy can result in an average levelized cost of $4.78 and 3.14 kg CO 2 -eq per kg H 2 ; (2) the frameworks for multiobjective optimisation and SCB maximisation are complementary because they prioritise different aspects to design the HSC. Taxes and surcharges for H 2 fuel will impact its final price at the refuelling station resulting in a higher TCO for FCVs compared to diesel buses and trucks in 2030 but the TCO becomes almost competitive for hydrogen trucks from 2035 when SCB is maximised. The SCB function can be refined and easily adapted to include additional externalities. [ABSTRACT FROM AUTHOR]