Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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 toward 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.
Drazen Dujic, Daniel Biner, Philippe Alexandre Bontemps
Mario Paolone, Elena Vagnoni, Francesco Gerini
Mario Paolone, Elena Vagnoni, Francesco Gerini