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 irradiation) 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 moving block bootstrap procedure is applied to generate time series for wind speed, solar irradiation, or temperature with hourly frequency, preserving temporal dependencies and addressing inherent seasonal trends. The approach allows simulation-based analysis of the impact of critical scenarios on different electric microgrids.

Marcon, G., Marletta, A., Moradi, S., Zizzo, G., Favuzza, S., Sottile, G. (2025). Time Series Bootstrap for Renewable Energy Analysis in Power Grid Optimization. In Statistics for Innovation III. SIS 2025, Short Papers, Contributed Sessions 2 (pp. 463-468) [10.1007/978-3-031-95995-0_77].

Time Series Bootstrap for Renewable Energy Analysis in Power Grid Optimization

Marcon, Giulia;Moradi, Salar;Zizzo, Gaetano;Favuzza, Salvatore;Sottile, Gianluca
2025-01-01

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 irradiation) 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 moving block bootstrap procedure is applied to generate time series for wind speed, solar irradiation, or temperature with hourly frequency, preserving temporal dependencies and addressing inherent seasonal trends. The approach allows simulation-based analysis of the impact of critical scenarios on different electric microgrids.
2025
9783031959943
9783031959950
Marcon, G., Marletta, A., Moradi, S., Zizzo, G., Favuzza, S., Sottile, G. (2025). Time Series Bootstrap for Renewable Energy Analysis in Power Grid Optimization. In Statistics for Innovation III. SIS 2025, Short Papers, Contributed Sessions 2 (pp. 463-468) [10.1007/978-3-031-95995-0_77].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/683770
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