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E-maintenance in hydropower energy generation: A case study of Enel Colombia

G. Cortés Sanchéz(1), G. Rodríguez Gómez(1), E. Guevara Pabón(1), T. Fontani(1), I. Durán Tovar(2), L. Benavides Navarro(2), A. Marulanda Guerra(2)

1. Enel Colombia O&M Hydro Colombia & Central America, Bogotá (Colombia)

2. Universidad Escuela Colombiana de Ingeniería Julio Garavito Bogotá (Colombia)

2026-01-20

Traditionally, maintenance in the hydropowerindustry has been a labour-intensive and time-consuming process. It often relies on scheduled inspections and manual intervention. E-maintenance in hydropower plants can help to address this challenge by allowing remote monitoring and control of plant equipment, enabling timely detection and diagnosis of potential problems. This paper presents a case study of the implementation of an e-maintenance strategy for hydropower infrastructure at one of the largest generation companies in the Colombian electricity market. A machine learning model, implemented by Enel Colombia, is fed with recorded data on turbine bearing temperature and active power generation to predict problems in hydropower generators. The results show how e-maintenance can reduce operating costs and avoid breakdowns in hydro generation.

Key words: E-maintenance, Hydro unit generator, Hydropower energy generation, Machine learning.

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