A0960
Title: Bootstrapping time series of renewable energy sources for environmental and energy studies
Authors: Giulia Marcon - Università degli studi di Palermo (Italy) [presenting]
Abstract: The increasing integration of renewable energy sources (RES) into power systems requires effective methods to handle their intrinsic variability, especially for small-scale systems like microgrids. These systems, often operating in islanded mode due to main grid disruptions, demand robust scenario-based analyses to ensure operational stability and energy resilience. A methodology is presented for generating synthetic time series of key meteorological variables (wind speed, solar irradiance, and temperature) used to model RES variability under diverse environmental conditions. The proposed approach employs a time series bootstrap technique, which preserves both short-term autocorrelations and seasonal patterns, while avoiding strong parametric assumptions. The resulting synthetic datasets enable the creation of multiple stochastic realizations, supporting environmental and energy studies focused on system reliability, performance evaluation, and risk assessment. These scenarios are particularly valuable for microgrid planning and operation, especially in isolated or fault-prone contexts. The method is being integrated into a broader framework for optimal energy storage utilization and microgrid reliability analysis under uncertainty.
