Sensitivity analysis of load profiles: Implications for resource adequacy in future power system

Ensuring the reliability of future electricity systems requires more than matching annual energy needs – it demands understanding when electricity is used. Traditional resource adequacy (RA) assessments rely on Monte-Carlo simulations across many climatic years to capture inter-annual variability, but often assume fixed demand profiles. This overlooks how even small structural shifts – such as increased heat pump use or changing EV charging patterns – can significantly alter system stress and operational outcomes. This study quantifies the sensitivity of RA metrics to such variations. Using ANTARES Simulator and the projection from the French Transport System Operation projections, a European electricity model for 2050 is developed and tested under three scenarios with equal annual demand but different hourly profiles: a reference case, a winter case (2–10 % more winter demand), and a peak case (5–20 % more peak-hour demand). Results show a 4 % winter load increase triples the Loss of Load Duration hours, and 8 % causes tenfold more unsupplied energy. Storage analysis reveals distinct limitations: winter scenarios are constrained by total energy availability, leading to longer events compare to peak scenarios, limited by discharge power and resulting in more frequent but shorter events. Importantly, most stress is concentrated in just a few critical climatic years. Identifying these years using simple indicators – like residual load or wind capacity factor – could reduce computational burden without losing key adequacy insights. This study emphasizes that alongside inter-annual variability, accounting for load shape sensitivity is essential for robust and reliable RA assessments in a changing energy system. • Traditional Resource Adequacy assessments often overlook structural changes in load profile variation. • A 4 % increase in the load in winter increase triples LOLD hours; an 8 % increase results in tenfold unsupplied energy. • Demand shifts must be considered alongside inter-annual climate variability in RA. • Simple metrics (wind factor, residual load) can flag critical years and cut computation.