Adaptive Robust Optimization for European Electricity System Planning Considering Regional Dunkelflaute Events
Maximilian Bernecker, Smaranda Sgarciu, Xiaoming Kan, Mehrnaz Anvari, Iegor Riepin, Felix M\"usgens

TL;DR
This paper presents an adaptive robust optimization model for planning a decarbonized European electricity system that accounts for regional Dunkelflaute events, revealing nonlinear cost impacts and the importance of cross-border infrastructure and flexible technologies.
Contribution
It introduces a novel capacity expansion model incorporating multiple extreme weather scenarios within a single optimization, enhancing resilience planning for renewable energy integration.
Findings
System costs increase nonlinearly with event extent, up to 71%.
Large-scale disruptions necessitate long-term hydrogen storage and load shedding.
Regional bottlenecks highlight the need for coordinated cross-border policies.
Abstract
The expansion of wind and solar power is driving the European energy system transformation, thereby also driving our reliance on this weather-dependent resources. Integrating renewable scarcity events into long-term planning has therefore become essential. This study demonstrates how worst-case regional renewable scarcity events - such as the Dunkelflaute, prolonged periods of low wind and solar availability - can be incorporated endogenously into the planning of a weather-robust, interconnected energy system. We develop a capacity expansion model for a fully decarbonized European electricity system using an adaptive robust optimization framework which incorporates multiple extreme weather realizations within a single optimization run. Results show that system costs rise nonlinearly with the geographic extent of these events: a single worst-case regional disruption increases costs by…
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Taxonomy
TopicsElectric Power System Optimization
