Operational Performance of ATRIA ENERGIA S.A.C.’s Micro-Hydroelectric Plant: Daily Generation Analysis (#1015)
Read ArticleDate of Conference
July 15-17, 2026
Published In
"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"
Location of Conference
Santiago (Chile)
Authors
Arellanos Tafur, Elmer
Abstract
This study presents a comprehensive analysis of the operational performance of ATRIA ENERGIA S.A.C.’s Purmacana micro-hydroelectric plant, based on 165 days of daily generation records from June 1, 2024, to May 31, 2025, with January 2025 excluded due to data unavailability. The 1.8MW facility, located in Supe district, Barranca province, Lima department, Peru, demonstrates highly variable operational characteristics with pronounced seasonal fluctuations. Daily energy production ranged from 0.10 MWh to 14.90 MWh, averaging 6.07 MWh with a standard deviation of 3.67 MWh (coefficient of variation: 60.5%). The plant achieved an actual capacity factor of 14.1%, substantially lower than the theoretical 71.3%, indicating significant operational constraints or data collection limitations. Monthly analysis revealed peak performance during October–November (19.7–24.6% capacity factor) and minimum performance during February–April (6.4–7.3% capacity factor), reflecting coastal Peru’s hydrological patterns. Performance distribution analysis showed that 62.4% of operations fell within normal parameters (μ } σ), 17.6% exceeded high performance thresholds, and 20.0% experienced low performance conditions. The projected annual generation of 2.22 GWh falls significantly below the expected 9 GWh, suggesting systematic data collection issues, extended maintenance periods, or fundamental operational challenges requiring investigation. These empirical findings provide critical insights for renewable energy planning, microhydroelectric plant optimization, and performance validation in Peru’s coastal region, particularly for facilities operating under the RER framework, while highlighting the importance of empirical validation of theoretical projections in developing economies.