Design of a future hydrogen supply chain: A multi-objective model for Turkey

Erdoğan A., GEÇİCİ E., GÜLER M. G.

International Journal of Hydrogen Energy, vol.48, no.31, pp.11775-11789, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 31
  • Publication Date: 2023
  • Doi Number: 10.1016/j.ijhydene.2022.12.071
  • Journal Name: International Journal of Hydrogen Energy
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Artic & Antarctic Regions, Chemical Abstracts Core, Communication Abstracts, Environment Index, INSPEC
  • Page Numbers: pp.11775-11789
  • Keywords: Hydrogen supply chain, Multi-objective optimization, Mixed integer linear programming
  • Yıldız Technical University Affiliated: Yes


© 2022 Hydrogen Energy Publications LLCOne of the important alternatives to conventional fossil fuel vehicles in the transportation sector is hydrogen fuel cell vehicle (HFCV) technology. One of the most significant obstacles to the widespread use of these vehicles is the hydrogen supply chain network (HSC) infrastructure. In the design of this network, the harm caused by the network to the environment and the security risks that may arise are as important as the associated cost of building it. In this study, an HSC design that will minimize cost, carbon emission and security risk for Turkey is proposed. The problem is modeled using a mixed integer linear programming (MILP). Five different optimization cases are studied when the penetration rate of HFCV is 25%. In the first three cases, the objectives are independently optimized. The multi-objective optimization is addressed in Case 4 and Case 5. Case 4 is solved with epsilon constraint method by employing the results of the first three cases. The most balanced solution found is 88%, 10% and 2% away from the best cost, carbon emission and risk values, respectively. It is observed that the proposed solution has a decentralized network structure where steam methane reforming (SMR) and electrolysis (ELE) production plants are established. In Case 5, the weighted sum method (another multi-objective optimization method) is used and those which gave the closest results to that of the epsilon constraint method are chosen as the associated weights of three objectives. Using these weights, 10 different demand scenarios are studied. It is observed that the HSC has a decentralized structure under almost all demand scenarios.