On the prediction of the induced damage by the start-up sequence of Francis turbines: On operational resilience framework

Martin Seydoux, Elena Vagnoni, Christophe Nicolet and Mario Paolone

Renewable Energy, 2024, vol. 228, issue C

Abstract: The number of transient operations in hydraulic machinery connected to power grid, notably start-ups and shut-downs, has observed a substantial increase in recent decades, primarily driven by the global shift towards intermittent renewable energy sources. Simultaneously, advancements in MW power converter technology and its cost-effectiveness have altered the operational paradigms of hydropower plants. These transformations offer novel opportunities for asset management within the industry. This study introduces a new method aimed at forecasting stress during start-up procedures, leveraging steady-state measurements acquired from a reduced scale model of the hydraulic turbine. Through a dedicated modular telemetry measurement system and the integration of strain gauges onto the reduced-scale runner blades, a tool is devised to predict dynamic loads characteristic of these transient operations. Utilizing steady-state measurements and a Voronoi cell tessellation, the transient predicted stress signal is constructed by concatenating the information from each encountered cell, thus providing an estimated projection of the stress likely to occur during the sequence. The proposed methodology demonstrates a robust forecast of the stresses on the runner blades during steady-state and transient operations of Francis turbines. Its immediate value lies in the ability to correctly estimate the lifetime of the runner as well as the possible integration into an optimization framework for stress reduction, thereby potentially extending the operational lifespan of the unit, from the runner structure perspectives.

Keywords: Francis turbine; Start-up sequences; Transient operations; Power stability; Damage evaluation; Stress forecasting (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:228:y:2024:i:c:s0960148124006554

DOI: 10.1016/j.renene.2024.120587

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