Abstract
A multiobjective optimization for improving the turbine output and efficiency of a counterrotating type pump-turbine unit operated at turbine mode was carried out in this work. The blade geometry of both the runners was optimized using a hybrid multiobjective evolutionary algorithm coupled with a surrogate model. Three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model were discretized by finite volume approximations and solved on hexahedral grids to analyze the flow in the pump-turbine unit. As major hydrodynamic performance parameters, the turbine output and efficiency were selected as objective functions with two design variables related to the hub profiles of both the runner blades. These objectives were numerically assessed at twelve design points selected by Latin hypercube sampling in the design space. Response surface approximation models for the objectives were constructed based on the objective function values at the design points. A fast nondominated sorting genetic algorithm for the local search coupled with the response surface approximation models was applied to determine the global Pareto-optimal solutions. The trade-off between the two objectives was determined and described with respect to the Pareto-optimal solutions. The results of this work showed that the turbine outputs and efficiencies of optimized pump-turbine units were simultaneously improved in comparison to the reference unit.
Highlights
To extract efficiently the renewable energy resources from nature such as hydro, wind, solar, and ocean, there have been increasing interests in the advanced technologies for the power stabilization system in the past several years
To carry out a multiobjective optimization, the response surface approximation (RSA) models for both objective functions were constructed by using the numerical results at twelve design points selected by Latin hypercube sampling (LHS)
As suggested previously by Giunta [26], these values are reliable according to the 0.9 < Ra2dj < 1.0 range to evaluate the accurate prediction of the RSA model
Summary
To extract efficiently the renewable energy resources from nature such as hydro, wind, solar, and ocean, there have been increasing interests in the advanced technologies for the power stabilization system in the past several years. Kanemoto and his colleagues [1,2,3] have proposed the newly power stabilization system by using the counterrotating type pump-turbine unit with the pumped storage. They demonstrated that this system can instantaneously stabilize the output from the unstable power station with a wind turbine by using the counterrotating type pump-turbine unit. This innovative technology is available for the wind power and all the foregoing renewable energies
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