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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.

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Time Series Bootstrap for Renewable Energy Analysis in Power Grid Optimization

  • 会议论文

  • 发表日期：

    2025年

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  • Giulia Marcon,
  • Andrea Marletta,
  • Salar Moradi,
  • Gaetano Zizzo,
  • Salvatore Favuzza,
  • Gianluca Sottile

摘要

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.