Small-scale hydropower generation can satisfy the needs of communities located near natural sources of flowing water. The operating conditions of a Michell–Banki Turbine (MBT) are relatively easier to meet than those of other types of turbine, making it useful in places where other devices are not suitable. Moreover, MBT efficiency is almost invariable with respect to flow rate conditions. Nevertheless, such efficiency commonly ranges between 70% and 85%, which is lower than that of other water turbines like Turgo, Pelton, or Francis turbine. The objective of this work is to determine the maximum theoretical efficiency of an MBT and its associated geometrical parameters by implementing Particle Swarm Optimization. The results show a higher effectiveness of the mathematical formulation compared with other cases from literature and show the performance of the optimization method proposed in this study in terms of solution and processing time. Finally, a maximum MBT efficiency of 93.3% was achieved

Small-scale hydropower generation can satisfy the needs of communities located near natural sources of flowing water. The operating conditions of a Michell–Banki Turbine (MBT) are relatively easier to meet than those of other types of turbine, making it useful in places where other devices are not suitable. Moreover, MBT efficiency is almost invariable with respect to flow rate conditions. Nevertheless, such efficiency commonly ranges between 70% and 85%, which is lower than that of other water turbines like Turgo, Pelton, or Francis turbine. The objective of this work is to determine the maximum theoretical efficiency of an MBT and its associated geometrical parameters by implementing Particle Swarm Optimization. The results show a higher effectiveness of the mathematical formulation compared with other cases from literature and show the performance of the optimization method proposed in this study in terms of solution and processing time. Finally, a maximum MBT efficiency of 93.3% was achieved.