Dış Kaynaklı Proje Süreçleri Yönetim Sistemi
Genç M. (Danışman (Yürütücü Gerçek Kişi Olan Projede)), Valasai G.
Turkey’s dependence on fossil-fuel imports and its position as Europe’s energy gateway require hydrogen pathways that are cost-competitive, climate-aligned, and resilient to infrastructure disruptions. Current hydrogen policies remain fragmented, and existing infrastructure faces exposure to earthquakes, grid outages, and extreme weather. This fellowship develops the first resilience-integrated MILP framework in Python (Pyomo/Gurobi) to generate a deployment roadmap for green hydrogen in Turkish smart cities.
The framework co-optimizes capacity planning and hourly dispatch while embedding four reliability metrics: SAIDI (System Average Interruption Duration Index, measuring average outage duration per customer), SAIFI (System Average Interruption Frequency Index, measuring average outage frequency per customer), EENS (Expected Energy Not Supplied, quantifying unmet demand), and LOLP (Loss of Load Probability, representing the likelihood of supply shortfalls). Stress tests include N-1 contingencies, 24-72 hour outages, earthquake scenarios, and heat waves. A geospatial pipeline (GeoPandas/rasterio) and machine-learning models (CatBoost) will identify priority hydrogen hubs in Istanbul, Izmir, Konya, and Kayseri under land-use, water, grid, and seismic constraints. Pandapower spot checks will verify feeder-level feasibility. The framework's resilience assumptions will be validated using synthetic outage data generated from public reports and established grid operating standards.
Deliverables include a 2030 Hydrogen & Resilience Roadmap, a Smart City Resilience Framework, and open repositories of code, data (CSV/YAML), and maps. The fellowship provides training in Pyomo/Gurobi optimization, geospatial analytics, and open-science practices, strengthening researcher capacity for ERC-level research and policy advisory roles aligned with EU decarbonization objectives.