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Comparative Analysis of Sampling Strategies for Solar Irradiance Signals and Their Implications in Discrete-Time Control Models

Research output: Contribution to journalArticlepeer-review

Abstract

This study compares uniform and stratified sampling strategies applied to hourly solar irradiance signals. The analysis examines how each approach affects signal reconstruction, anomaly detection, and dynamic PV modelling. Using PCHIP interpolation and error metrics such as RMSE and MAE, results show that uniform sampling yields lower global reconstruction error (26.64 W/m2 vs. 32.98 W/m2), while stratified sampling captures instantaneous peaks more accurately under high-variability conditions. Stratified sampling also improves anomaly identification due to its more representative temporal distribution. These findings highlight a practical trade-off between minimizing average error and preserving extreme events, providing guidance for PV estimation, forecasting, and discrete-time control applications.

Original languageEnglish
Article number1348
JournalEnergies
Volume19
Issue number5
DOIs
StatePublished - Mar 2026

Bibliographical note

Publisher Copyright:
© 2026 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • discretisation
  • MATLAB R2025b
  • photovoltaic generation
  • sampling
  • solar irradiance
  • statistical analysis

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