Abstract
In this paper we compare two cutting-edge timeperiod aggregation methodologies for power system models that consider both renewables and storage technologies: the chronological time-period clustering; and, the enhanced representative period approach. Such methodologies are used in order to reduce the computational burden of highly complex optimization models while not compromising the quality of the
results. With this paper, we identify which method works best, and under which conditions, in order to reproduce the outcomes of the hourly benchmark model.
What time-period aggregation method works best for power system operation models with renewables
and storage?
