A1721
Title: Generating time series for renewable energy analysis in power grids through bootstrap
Authors: Andrea Marletta - Università degli Studi di Palermo (Italy) [presenting]
Giulia Marcon - Università degli studi di Palermo (Italy)
Gianluca Sottile - University of Palermo (Italy)
Abstract: As renewable energy becomes an increasingly important factor in electricity generation, accounting for the variability of its primary sources (such as wind speed and solar irradiance) is essential in energy grid design and power system analysis. In this context, simulating time series of renewable energy sources that reflect the characteristics of the original data helps understanding the impact of this variability on grid performances. A block bootstrap variant procedure is proposed to generate time series for wind speed, solar irradiance, or temperature with hourly frequency, addressing inherent seasonal trends. Data results as sufficiently representative, then simulated series exhibit similar behavior to the original input series. In order to check the adequacy of the proposed model, the evaluation of the procedure involves the main statistical properties such as mean, variance, and autocorrelation function which were compared between the original and simulated series. The approach allows simulation-based analysis of the impact of critical scenarios on different electric grids.
