Coupled Multipoint Shape Optimization of Runner and Draft Tube of Hydraulic Turbines

Abstract

This paper suggests a method of simultaneous multi-objective shape optimization of hydraulic turbine runner and draft tube (DT) with the objective to increase turbine efficiency in wide range of operating points (OPs). Runner and DT are the main sources of energy losses in hydraulic turbines. Coupling runner and DT in computational fluid dynamics (CFD) analysis enables correct statement of boundary conditions for efficiency evaluation, while simultaneous variation of these components allows more flexible adjustment of flow passage geometry. Detailed runner parameterization with 28 free geometrical parameters and DT parameterization with nine free parameters are given. Optimization problem is solved using multi-objective genetic algorithm (MOGA). For each variation of runner and DT shapes, flow field in wicket gate (WG), runner, and DT is simulated using steady-state Reynolds-Averaged Navier–Stokes (RANS) equations with k-e turbulence model. Energy-based boundary conditions are used for the calculations, allowing determination of efficiency of the whole turbine in correspondence with International Electrotechnical Commission (IEC) standard. Formulations of multiple OP efficiency objective functions and constraints are discussed in detail. To demonstrate the advantages of simultaneous runner and DT variation, two optimization problems are solved for a medium specific speed Francis turbine. Namely, single runner and coupled “runner–DT” optimizations are carried out. It is shown that optimized runner–DT geometry outperforms the result of single runner optimization by about 0.3% in terms of average efficiency, showing the potential of the developed approach to improve multiregime turbine characteristics in practical design optimization problems.

Optimization procedure for variable speed turbine design

“…Several examples of Francis turbine runner optimization exist (Enomoto, Kurosawa, & Kawajiri, 2012;Nakamura & Kurosawa, 2009;Pilev et al, 2012), some even optimizing the runner and draft tube simultaneously (Lyutov, Chirkov, Skorospelov, Turuk, & Cherny, 2015). Most of these attempts deal with medium-to-high specific speed Francis turbines, but other turbine types have also been optimized using similar techniques (Ezhilsabareesh, Rhee, & Samad, 2018;Semenova et al, 2014).…”

“…Most of these attempts deal with medium-to-high specific speed Francis turbines, but other turbine types have also been optimized using similar techniques (Ezhilsabareesh, Rhee, & Samad, 2018;Semenova et al, 2014). The peak efficiency of hydro turbines has not increased much in the last decades, as noted in Electric Power Research Institute (1999) and Lyutov et al (2015). Instead, optimization attempts usually aim to increase the efficiency away from the best operating point.…”

Automated Design for Microfluid Flow Sculpting: Multiresolution Approaches, Efficient Encoding, and CUDA Implementation

“…Stoecklein et al [6] tackled the inverse problem in pillar programming by using an off-the-shelf GA, 2 which has been previously used to optimize the geometry for the fluid flow applications [12][13][14][15]. The encoding of the design variables (a "chromosome" in the GA) was a set of integers, each of which acted as an index representing a micropillar configuration (i.e., a micropillar of some diameter and position for set flow conditions and channel geometry).…”

Scenarios for refurbishment of a hydropower plant equipped with Francis turbines

“…It is the most efficient way to generate electricity and/or to regulate grid. Therefore, the technical solutions in order to refurbish the old hydropower plants are challenging task [1][2][3][4][5][6]. The main constrains are revealed in limitations of the hydropower plant operation [7,8].…”