Evaluating the predictive potential of modeling frameworks for Pelton turbine energy performance and guiding engineering modeling in hydroelectric applications

Amid the growing global emphasis on energy conversion technologies and the increasing promotion of renewable energy, Pelton turbines play a pivotal role in energy transformation, particularly in hydropower development in western China. Accurate modeling is essential for understanding the energy performance of Pelton turbines. However, a critical gap in current research is the absence of a systematic evaluation to clarify the differences among various modeling frameworks. This study focuses on China's largest under-construction Pelton turbine, employing numerical simulations with the SST k-ω turbulence model and a homogeneous multiphase flow model under the Euler-Euler framework to analyze the predictive potential of key parameters within the numerical modeling framework—time step and different geometric modeling frameworks on energy performance. The results demonstrate: (1) A Courant number less than 5 balances computational accuracy and efficiency in time-step selection. (2) Symmetric modeling framework overestimates hydraulic efficiency by neglecting pseudo-symmetric biases in jet velocity distribution, while full modeling framework reveals asymmetric power allocation. (3) Inlet loop pipe design reduces efficiency by approximately 0.40 % through jet deflection at nozzle exit. This study highlights the necessity of selecting appropriate modeling frameworks for reliable Pelton turbine performance prediction.