Daily Energy Production Patterns in Medium-Scale Hydroelectric Operations: A Longitudinal Descriptive Study

Arellanos-Tafur E.; Damas-Niño M. · Proceedings of 2025 International Conference on Artificial Intelligence, Embedded Systems, and Renewable Energy, AIESRE 2025 (2025) · DOI: 10.1109/aiesre67541.2025.11470156

Resumen

The present research addresses the limited documentation of daily energy generation patterns in medium-scale hydroelectric plants within current literature. It analyzes a 14 month dataset (from April 2024 to May 2025) from a representative 4 MW facility in Peru, comprising 404 consecutive daily observations. The temporal variability identified in these records provides valuable insights into broader operational dynamics. Statistical analysis revealed distinct seasonal fluctuations, with an average daily production of 80.70 MWh(σ=8.04). The coefficient of variation (9.96%) denotes stable operational performance throughout the observation period. Monthly distributions exhibited significant differences, with optimal performance during winter months (mean =82.38 MWh, CV =5.67%) and increased variability during summer period (mean =78.15 MWh, CV=8.67%). Maximum outputs reached 89.40 MWh and minimum levels reached 11.75 MWh. The interquartile range (79.34-84.90 MWh) indicates concentration of generation near the facility's optimal efficiency envelope. These results suggest that the observed patterns arise from the interaction of hydrological availability, operational scheduling, and maintenance protocols. The empirical characterization provides baseline indicators for comparative evaluations and operational optimization, while emphasizing the necessity of incorporating meteorological variables and multi-facility datasets in future investigations.

Instituciones: Universidad Continental; Universidad Nacional del Callao