Gorde:
| Egile Nagusiak: | , , |
|---|---|
| Formatua: | Recurso digital |
| Hizkuntza: | ingelesa |
| Argitaratua: |
Zenodo
2025
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| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.5281/zenodo.17400949 |
| Etiketak: |
Etiketa erantsi
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Aurkibidea:
- <p>This dataset contains over 2.5 million real-world measurements collected from a photovoltaic (PV) inverter system between 2023 and 2025. The data were recorded as part of research on solar energy forecasting, energy-aware intermittent computing, and predictive checkpointing for IoT nodes.</p> <p>Measurements were acquired from a SH10RT inverter system equipped with dual MPPT channels and three-phase output monitoring. Each record includes synchronized current and voltage readings captured at high temporal resolution, supporting studies in energy forecasting, digital twins, and low-power system optimization.</p> <p>The dataset is divided into two major components merged by timestamp:<br><strong>Current dataset</strong> — MPPT and phase current readings<br><strong>Voltage dataset</strong> — MPPT, phase, and battery voltage readings</p> <p><strong>File Structure</strong><br>- `solar_data_2023_2025.csv.gz` — full merged dataset (compressed)<br>- `sample_10k.csv` — 10,000-row subset for testing and analysis<br>- All timestamps are stored as UTC datetime converted from nanosecond epoch.</p> <p><strong>Applications</strong><br>- Solar energy forecasting (short-term and day-ahead)<br>- Energy-aware and intermittent system modeling<br>- Battery and inverter performance analytics<br>- Edge intelligence and digital twin simulation</p> <p><strong>Citation</strong><br>If you use this dataset, please cite:<br>> Abubakar, J. A. (2025) et al. <em>Solar Energy Harvesting Dataset (2023–2025)</em>. Zenodo. https://doi.org/10.5281/zenodo.17400949</p> <p><strong>License</strong><br>Released under the <strong>Creative Commons Attribution 4.0 International (CC BY 4.0)</strong> license. This allows for free use, redistribution, and adaptation with appropriate credit.</p> <p><strong>Acknowledgment</strong><br>Data collected within the research framework on predictive energy-aware computing and solar-powered IoT systems, University of Bremen.</p>