Event-Enriched Temporal Aggregation for Wind–Solar–Storage Planning: Out-of-Sample Evidence

Representative-day models can underestimate long-duration storage requirements because independent daily cycles fragment multi-day renewable shortages. This study proposes an event-enriched temporal aggregation method that retains load-weighted low-availability events as contiguous windows while keeping the modeled horizon fixed at 2160 h. Using German hourly wind, photovoltaic, and load profiles, capacity decisions are optimized on 2017–2018 data and evaluated chronologically on unseen 2019 data. Compared with conventional representative days, event enrichment increases the planned storage energy from 7.474 to 36.023 MWh and reduces its deviation from the 42.416 MWh full-chronology solution from 82.38% to 15.07%. In out-of-sample operation, energy not served decreases from 19.164 to 1.773 MWh, representing a 90.75% reduction, while annualized evaluation cost falls by 22.83%. Lower energy not served is obtained for all six clustering seeds and across the tested storage-cost range. Sensitivity analyses indicate that the benefit depends on the planning shortage allowance and on whether the historical record contains events relevant to the evaluation year. Therefore, retaining selected multi-day shortages improves storage-capacity fidelity and out-of-sample ENS performance without increasing the temporal budget.