Representing net load variability in electricity system capacity expansion models accounting for challenging weather-years

Cost-minimizing electricity system models are important tools for understanding conditions for the development of the electricity system. Since the variability of wind and solar power outputs differs between years, a satisfactory representation of variability requires a high time resolution, as well as data that cover multiple decades. This work proposes a weather-year selection method that represents power generation variability by selecting a set of weather years to represent the net-load variability of a broader span of historical weather years (in this work, 39 years). The representativeness is captured in terms of net-load amplitude and duration, such that the electricity demand, as well as the wind- and solar-generation profiles, are considered in their chronologic order, rather than simply as discrete data-points. The weather-year selection method is applied to modeling the North European electricity system with the aims of evaluating the method and investigating the impacts of extreme net-load events on the electricity system composition. The results show that the proposed method can represent the net-load variability of multiple decades using a few selected weather-years. In addition, when the probability of extreme net-load events is accounted for, these extreme events mainly increase the peak thermal capacity and long-term biogas fuel storage capacity.