Optimization method for the design of axial hydraulic turbines

Abstract

Computational fluid dynamics (CFD) is becoming an increasingly reliable tool for the design of water turbines. Using different CFD codes, it is possible to find out and compare criteria for classifying runner blade geometry regarding the strengths of their characteristics. The final decision of runner geometry, with demanding energetic and cavitation characteristics, always remains for the design engineer. To reach the final result, the engineer has to compare the flow analysis results of a great number of different geometries. To replace a part of this work, an optimization algorithm has been developed. This optimization procedure helps to check many more geometries with less human work. In this paper, a multiobjective genetic algorithm for the design of axial runners is presented. For the flow analysis, the CFX-TASC flow code, with a standard k-ɛ turbulence model, has been used, because the code enables calculation within a rotating frame of reference. For design of the initial geometry, within the optimization procedure, a special program has been developed, which makes it possible to start the optimization procedure with a relatively high level of efficiency and transforms prescribed genetic parameters to the runner geometry.

Performance Analysis of Axial and Mixed Flow Turbines: A Comparative Study

“…The discharge factor variation in Francis turbine with speed is negligible but increases with guide vane opening while in case of Kaplan turbine it increases with increase in both speed and guide vane opening as seen in fig. 9(a) and 9(b) [1]. The hydraulic efficiency has parabolic variation for each guide vane with maximum efficiency at different speed factors as shown in fig.…”

“…Reaction turbines are classified as mixed flow (Francis turbine) and axial flow (Propeller Kaplan turbines). The Francis and propeller runners have fixed blades and Kaplan runner has adjustable blade [1]. Theses turbines are mounted horizontally or vertically depending on the operational requirements.…”

Optimization of the Runner for Extremely Low Head Bidirectional Tidal Bulb Turbine

“…Many studies have focused on optimization of runners for Kaplan, Francis, pump-turbine, and unidirectional bulb turbines with large capacity using the CFD (computational fluid dynamics) method coupled with optimization algorithms. Lipej [8] presented a multi-objective genetic algorithm for the design of axial runners. Within the optimization procedure, a special program has been developed, which makes it possible to start the optimization procedure with a relatively high level of efficiency and transforms prescribed genetic parameters to the runner geometry.…”

Effect of Intake Vortex Occurrence on the Performance of an Axial Hydraulic Turbine in Sihwa-Lake Tidal Power Plant, Korea

“…Lipej [10] optimized the design of the runner blade to maximize the hydrodynamic performance of an axial hydraulic turbine by using a multi-objective evolutionary algorithm. Lee at al.…”