Lifetime analysis of hydro turbines with focus on fatigue damage in a renewable energy system – A review

With the increasing share of intermittent renewable electric energy sources, such as wind and solar power, the electric grid risks becoming imbalanced. In regions where hydropower provides a significant share of the renewable electric power production, hydropower has a great potential to mitigate some of this imbalance through flexible and fast-responsive operation. This involves frequent starts and stops, continuous regulation, and off-design operating conditions, for which the machines were not designed. New questions arise for hydropower, such as how much the lifetime of the machines is reduced, how the maintenance intervals should be determined, the costs, and the limits of safe operation. This review paper investigates the extent to which lifetime analysis has been used to answer these questions whenever hydropower is used to stabilize a renewable electric energy system. The focus is on fatigue damage, which is a lifetime reduction mechanism strongly connected to the new kind of operation of hydraulic turbines in a renewable energy system. The review summarizes both experimental and numerical methods and lists the alternative steps required for a complete lifetime analysis of hydro turbines. It is found that a few studies do indeed indicate quantitatively that the lifetime of hydraulic turbines is reduced by operating at off-design, but most studies do not come close to a complete lifetime prediction. This reveals an important gap in research and highlights the need for further studies that quantitatively answer the questions related to potential problems for hydropower as a regulating resource in a renewable electric energy system. • Summarizes procedures for lifetime estimations of hydro turbines. • Categorizes experimental and numerically based fatigue damage calculation methods. • Reveals a lack of complete residual lifetime calculations in the literature. • Points out directions for future hydro turbine lifetime analysis.