Adaptive Robust Optimization for European Electricity System Planning Considering Regional Dunkelflaute Events

This repository encompasses a capacity expansion model that identifies the worst-case regional "Dunkelflaute" events — prolonged periods of low wind and solar availability — and incorporates them into the optimization process. Furthermore the deterministic counterpart is provided, which indentifies hte optimal generation capacity mix based on an average weather year.

Model, Code, Solver and Data

The optimization problem is formulated with GAMS. Gurobi version 11.0 (Barrier algorithm) is used to solve the optimization problem. The data for both models are stored in a excle file:

• Deterministic model: Data_Input.xlsx
• ARO model: Data_Input_ARO.xlsx

Specifications Adaptive Robust Optimization Model:

Gurobi solver parameters:

• Primal Problem: Method=2, BarConvTol = 0, Crossover = 0
• Dual Problem: ScaleFlag = 1, Barhomogeneous = 1, NumericFocus =1, Presolve=2, BarConvTol = 0.0

The uncertainty buget must be adjusted mannualy within the GAMS code - section: line 869 - line 884

Consideration:

• A system of 24 EU countries an 50 nodes
• Renewable electricity generation resources like solar PV, wind-onshore, wind-offshore, run of river and hydro reservoirs
• Storages like lithium battery, hydrogen and hydro pumping storage plants
• High voltage electricity grid - power flow is modelled using linearizied DC OPF
• Future synthetic country demand profiles
• Wind and PV generation capacity profiles from renewables ninja
• Country specific hydro generation potentials

Map of the Base System