Exploring the sensitivity of capacity configuration for multi-energy complementary system across multi-temporal scales

Multi-energy complementary systems that integrate wind, solar, and hydropower have become crucial for enhancing energy supply efficiency and stability. However, existing capacity configuration frameworks for these systems often rely on deterministic, single-temporal-scale methods. This study investigated the sensitivity of capacity configurations in these types of integrated systems based on spectral characteristic analysis of renewable energy outputs under different time scales. A multi-temporal-scale capacity optimization model was developed to quantify the maximum energy storage capacity required for stable operation of the power grid under different combinations of renewable capacities. Sensitivity analysis was used to evaluate the relative impacts of solar and wind power capacities on energy storage requirements. The results show that solar power exhibits predominantly mid-frequency fluctuations, wind power demonstrates complex multi-band variability, and hydropower maintains stable low-frequency output patterns. Expanding the hydro-power capacity reduces considerably the energy storage demand, whereas wind power capacity has emerged as the primary determinant of storage requirements, particularly under constrained hydro-power regulation scenarios. Notably, the influence of solar power capacity on storage needs becomes increasingly pronounced at higher hydro-power penetration levels. These findings emphasize the critical role of strategic hydro-power capacity allocation in mitigating wind power intermittency and improving systemic stability.