Sustainable and Resilient Hydrogen Supply Chain Planning Under Uncertainty: A Stochastic Multi-Period Case Study of the Marmara Region
Sustainability (Switzerland), cilt.18, sa.12, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 18 Sayı: 12
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/su18126112
- Dergi Adı: Sustainability (Switzerland)
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, CAB Abstracts, Geobase, INSPEC
- Anahtar Kelimeler: disaster resilience, energy transition, hydrogen supply chain, multi-period planning, stochastic optimization, Variable Neighborhood Search
- Yıldız Teknik Üniversitesi Adresli: Evet
Özet
Hydrogen (H2) is regarded as a promising option for sustainable energy systems; however, its large-scale use in electricity supply remains limited. This study develops a stochastic network optimization model to examine the applicability of H2-based electricity generation. The proposed Hydrogen Supply Chain (HSC) model evaluates cost and emission performance under uncertainty by considering disaster conditions, transmission losses, depreciation, and the time value of money. The Marmara Region of Türkiye is divided into 24 grid nodes, and a single-period model for 2023 is solved using Mixed-Integer Linear Programming (MILP). The HSC is allowed to meet 10–40% of electricity demand and to replace collapsed grid lines by supplying critical public centers (CPCs) during disasters. The results show that the HSC can meet 24.82% of demand, although at costs approximately 3.9 times higher than power grid (PG) electricity, while producing 3.44 MtCO2/year compared to 65.96 MtCO2/year from the PG. The model is then extended to a multi-period structure (2023–2053) and solved by Variable Neighborhood Search (VNS). Over time, H2 costs decline, and their share rises from 19% to 35%, while electricity costs decrease from 408 USD/MWh to 170 USD/MWh. These findings suggest that H2-based electricity supply can support long-term sustainability and resilience objectives in regional energy planning.