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 language | English |
|---|---|
| Article number | 1348 |
| Journal | Energies |
| Volume | 19 |
| Issue number | 5 |
| DOIs | |
| State | Published - Mar 2026 |
Bibliographical note
Publisher Copyright:© 2026 by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- discretisation
- MATLAB R2025b
- photovoltaic generation
- sampling
- solar irradiance
- statistical analysis
Fingerprint
Dive into the research topics of 'Comparative Analysis of Sampling Strategies for Solar Irradiance Signals and Their Implications in Discrete-Time Control Models'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver