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https://accedacris.ulpgc.es/jspui/handle/10553/154905
| Título: | Experimental dataset of charge and discharge patterns in a 1200Ah OpzS battery bank | Autores/as: | Rocha Henríquez, Francisco Javier Aguasca Colomo, Ricardo Méndez Babey, Máximo |
Clasificación UNESCO: | 33 Ciencias tecnológicas | Palabras clave: | Probabilistic genetic algorithms OPzS lead-acid batteries State of charge estimation Voltage prediction Renewable energy storage |
Fecha de publicación: | 2025 | Publicación seriada: | Data in Brief | Resumen: | This dataset was generated from experiments on a bank of six 1200 Ah OPzS stationary batteries connected in series to form a 12 V storage system. Each cell was monitored for voltage, temperature, and electrolyte density using a DataTaker DT85M recorder, complemented by Pt100, analog voltmeters, and Hall effect sensors. Charging was performed with a programmable DC power supply under conventional, photovoltaic, and wind profiles, while discharging used a programmable electronic load capable of reproducing C10 and C20 curves, real consumption patterns from Gran Canaria, and random pulse sequences. Data were collected at one-minute intervals between August 2024 and May 2025, covering 1375 h and 42 min. The dataset includes 14 charge–discharge cycles, with 1053 to 13,385 records per cell. Provided in CSV format, the dataset enables straightforward processing and supports applications in battery modeling, comparative performance analysis, and validation of energy management algorithms. | URI: | https://accedacris.ulpgc.es/jspui/handle/10553/154905 | ISSN: | 2352-3409 | DOI: | 10.1016/j.dib.2025.112308 |
| Colección: | Artículos |
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