Author(s): Alessandra Conti and Marco Bianchi

Abstract: Run-of-river (RoR) hydropower systems represent a critical component of renewable energy generation, yet their operational efficiency often fluctuates due to variable hydraulic conditions, sediment load, and site-specific head variations. This study focuses on the optimization of turbine performance in RoR installations using computational fluid dynamics (CFD) modeling as a predictive and design enhancement tool. A medium-head RoR turbine was modeled and analyzed through ANSYS Fluent employing the Shear Stress Transport (SST) k-? turbulence model to simulate internal flow characteristics, pressure distribution, and cavitation tendencies. The geometry of the runner blades, hub-to-tip ratio, and wicket-gate angles were systematically varied and optimized using multi-objective response surface methodology and design of experiments (DOE) techniques. Statistical analysis through ANOVA confirmed the significance of geometric parameters on turbine efficiency (p < 0.001), with wicket-gate opening and blade stagger identified as dominant factors. The optimized turbine demonstrated a 3-5% increase in hydraulic efficiency and improved cavitation performance compared to the baseline model, achieving smoother velocity profiles and reduced flow separation under both design and off-design conditions. The paired t-test confirmed the statistical robustness of the improvement, while cavitation number (?) analysis indicated enhanced pressure distribution and stability across flow variations. The findings validate CFD-driven optimization as an effective approach for tailoring turbine designs to real-world hydraulic variability in RoR plants. The study concludes with practical recommendations emphasizing CFD integration in the early design phase, periodic hydraulic diagnostics, adaptive gate mechanisms, and sediment-aware design protocols to ensure sustainable, high-performance operation. The outcomes provide a replicable digital framework for developing efficient and resilient hydropower turbines adaptable to diverse hydrological environments.

Pages: 26-32 | Views: 5 | Downloads: 4

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