📝 SummarXiv

Abstract

Future greenhouse gas neutral energy systems will be dominated by renewable energy technologies whose energy output and utilisation is subject to uncertain weather conditions. This work proposes an algorithm for capacity expansion planning if only uncertain data is available for a year's operative parameters. When faced with multiple possible operating years, the quality of a solution derived on a single operating year's data is evaluated for all years, and the optimisation problem is iteratively modified whenever supply gaps are detected. These modifications lead to solutions with sufficient back-up capacity to overcome periods of cold dark lulls, and sufficient total annual energy supply across all years. A computational study on an energy system model of Germany for 40 different operating years shows that the iterative algorithm finds solutions that guarantee security of supply for all considered years increasing the total annual cost by 1.6-2.9% compared to a lower bound. Results also underline the importance of assessing the feasibility of energy system models using atypical time-series, combining dark lull and cold period effects.