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See discussions, stats, and author profiles for this publication at: http://www.researchgate.net/publication/278737864

A selected literature review of efficiency improvements in hydraulic turbines

 ARTICLE  in  RENEWABLE AND SUSTAINABLE ENERGY REVIEWS · JUNE 2015

Impact Factor: 5.9 · DOI: 10.1016/j.rser.2015.06.023

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4 AUTHORS, INCLUDING:

Xin Liu

Tsinghua University

8 PUBLICATIONS  3 CITATIONS 

SEE PROFILE

 Yongyao Luo

Tsinghua University

29 PUBLICATIONS  54 CITATIONS 

SEE PROFILE

Bryan W Karney

University of Toronto

369 PUBLICATIONS  1,403 CITATIONS 

SEE PROFILE

Available from: Xin Liu

Retrieved on: 16 October 2015

http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_4http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_5http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_5http://www.researchgate.net/?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_1http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/institution/University_of_Toronto?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_6http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_5http://www.researchgate.net/profile/Bryan_Karney?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_4http://www.researchgate.net/profile/Yongyao_Luo?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/institution/Tsinghua_University?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_6http://www.researchgate.net/profile/Yongyao_Luo?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_5http://www.researchgate.net/profile/Yongyao_Luo?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_4http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_7http://www.researchgate.net/institution/Tsinghua_University?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_6http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_5http://www.researchgate.net/profile/Xin_Liu110?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_4http://www.researchgate.net/?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_1http://www.researchgate.net/publication/278737864_A_selected_literature_review_of_efficiency_improvements_in_hydraulic_turbines?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_3http://www.researchgate.net/publication/278737864_A_selected_literature_review_of_efficiency_improvements_in_hydraulic_turbines?enrichId=rgreq-1a55565b-e2d5-4687-8377-dd933073d3a7&enrichSource=Y292ZXJQYWdlOzI3ODczNzg2NDtBUzoyNDI3NzU2MTQ1NTQxMThAMTQzNDg5MzYyNTE4Mg%3D%3D&el=1_x_2

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A selected literature review of ef ciency improvementsin hydraulic turbines

Xin Liu a, Yongyao Luo a, Bryan W. Karney b,n, Weizheng Wang a

a Department of Thermal Engineering, Tsinghua University, Beijing 100084, Chinab Department of Civil Engineering, University of Toronto, 35 St. George St., Toronto, Canada ON M5S 1A4

a r t i c l e i n f o

 Article history:

Received 21 October 2014Received in revised form

27 April 2015

Accepted 1 June 2015

Keywords:

Hydraulic turbines

Ef ciency losses

Performance testing

CFD method

Ef ciency improvement

a b s t r a c t

Knowing the ef ciency of a hydraulic turbine has important operational and nancial benets to those

who operate a plant. Historical ef ciency and other data on turbine performance are essential for theinformed selection and use of turbines. So having such a database from different manufactures is

attractive. However, at present it is almost impossible to get a universal database to reect the turbine

characteristics. This paper reviewed a set of empirical equations to replacefull database which de nes

the peak ef ciency and shape of the ef ciency curve as a function of the commissioning date for the unit,

rated head, rated  ow and other main design parameters. Since the design theories, methods and tools

of turbines are relatively mature, and the majority of turbine manufacturers have reached a level of 

know how which enables them to carry out hydraulically and structurally correct units to product high-

performance turbines. This paper paid more attention to the design factors, which could inuence the

value of the practically attainable overall turbine ef ciency. To quantify the effects of these factors, this

paper investigated the inuence of roughness and gap clearances on the internal leakage   ow rate.

Testing and CFD are the most two important tools in different design stages. This paper reviewed some

key ideas and issues on the ef ciency research in both. At last, improvement measures based on these

above mentioned design factors were provided.

&   2015 Elsevier Ltd. All rights reserved.

Contents

1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2. Mathematical model for predicting turbine ef ciency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3. Design factor affecting turbines ef ciency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2. Inuence of surface roughness and wear. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3.3. Inuence of gap clearances on the internal leakage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.4. Others. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4. Performance testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.1. Model tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.2. Field tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244.3. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5. CFD method for promoting the research and design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.1. Improving pressure recovery in draft tube. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.2. Cavitation research by CFD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.3. CFD in tip clearance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5.4. Prediction of erosion in hydraulic turbines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5.5. CFD in off-design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5.6. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Contents lists available at  ScienceDirect

 jo ur nal ho me pag e:  www.elsevier.com/locate/rser

Renewable and Sustainable Energy Reviews

http://dx.doi.org/10.1016/j.rser.2015.06.023

1364-0321/& 2015 Elsevier Ltd. All rights reserved.

n Corresponding author. Tel.:  þ1 416 9787776.

E-mail address: karney@ecf.utoronto.ca (B.W. Karney).

Renewable and Sustainable Energy Reviews 51 (2015) 18–28

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://www.sciencedirect.com/science/journal/13640321http://www.elsevier.com/locate/rserhttp://dx.doi.org/10.1016/j.rser.2015.06.023mailto:karney@ecf.utoronto.cahttp://dx.doi.org/10.1016/j.rser.2015.06.023http://dx.doi.org/10.1016/j.rser.2015.06.023http://dx.doi.org/10.1016/j.rser.2015.06.023http://dx.doi.org/10.1016/j.rser.2015.06.023mailto:karney@ecf.utoronto.cahttp://crossmark.crossref.org/dialog/?doi=10.1016/j.rser.2015.06.023&domain=pdfhttp://crossmark.crossref.org/dialog/?doi=10.1016/j.rser.2015.06.023&domain=pdfhttp://crossmark.crossref.org/dialog/?doi=10.1016/j.rser.2015.06.023&domain=pdfhttp://dx.doi.org/10.1016/j.rser.2015.06.023http://dx.doi.org/10.1016/j.rser.2015.06.023http://dx.doi.org/10.1016/j.rser.2015.06.023http://www.elsevier.com/locate/rserhttp://www.sciencedirect.com/science/journal/13640321http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-

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6. Ef  ciency improvement in turbines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

6.1. Better design or optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

6.2. Improve the surface performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

6.3. Improvements to hydropower production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

7. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

1. Introduction

Hydropower has been a proven, extremely   exible, and well-

advanced technology for more than one century. At present, its

technology is very mature. Still, there is some room for further

improvements. Turbine ef ciency is likely the most important

factor in a unit. As the heart of the system, design of a turbine is

focused on this to obtain the maximum ef ciency. The maximum

ef ciency can be reached when all losses are kept to a minimum.

In general, peak ef ciencies of Francis turbines with modern

design tools like CFD method have enabled to achieve the range of 

93% to almost 96%. The position that peak ef ciency occurs varies

between 80% and 95%  ow. For Kaplan turbine, the position thatpeak ef ciency occurs varies between 94% and 100%   ow. Ef -

ciency loss at higher heads drops 2 to 5 percent points below peak

ef ciency at the design head, and as much as 15 percent points at

lower heads. For multi-nozzles Pelton turbines, the high ef ciency

zones are even broader due to the number of operating jets can be

varied. The position that peak ef ciency occurs varies between

65% and 80%  ow. Crossow turbines are only used in the lower

power range. Generally, large turbine refers to single unit with a

capacity of more than 50,000 kW, and small turbine refers to unit

capacity of 100 kW to 50,000 kW. Turbines can reach high ef -

ciency under normal circumstances, but rather low ef ciency

during small   ow rate. With total ef ciencies from 84% to 87%

[1], the peak ef ciency is a little less than that of other turbines.

2. Mathematical model for predicting turbine ef ciency 

It is dif cult to  nd out on turbine ef ciency data in detail in

most paper, while manufacturers are reluctant to divulge data.

Since manufacturers regard such information as proprietary that

could compromise a competitive advantage. So in some cases it is

challenging and not  exible to obtain the turbine ef ciency due to

time, budgetary, or other constraints. J.L Gordon   [2]   did a very

good job to develop a set of empirical equations for calculation of 

turbine runner ef ciencies, taking the increase in ef ciency of 

newer designs and deterioration since commissioning into

account. The method outlined by Gordon is a generic procedure,

with calibration factors for different turbines. The accuracy of 

Gordon's method is within  73%. These equations are intended as

an aid in

  Estimating new runner performance at the feasibility studystage and

 Estimating old runner performance where it is impractical toundertake ef ciency tests or where commissioning test records

are unavailable.

At last, these equations with their plotting curves are very

useful to help understand the development of the ef ciency level

of turbines, and different ef ciency characteristics of different

types of turbines.

For reaction runners, the peak ef ciency equation has the

following form:

ε peak ¼ AΔε year Δεspecificspeed þΔεsize   ð1Þ

where A  is a constant value depending on the type of the runner;

Δε year    is the ef ciency change due to the year the unit was

commissioned; Δεspecificspeed  is the ef ciency change due to specic

speed; and Δεsize  is the ef ciency change due to size.

This equation indicates that four parts inuence the peak

ef ciency. The  rst one  xed the base level of the peak ef ciency.

Based on the statistics of a large sample of data in a lot of 

operating hydropower plants, A  has a value of 0.9187 for a Francis

runner and 0.904 for Kaplan and axial  ow runners. The difference

in the base level is 1.47%, double the 0.75 difference given in ASME

data   [3]. The second one shows the difference in ages and

commissioning. The   rst three parts determine the peak model

ef ciency. And the last one is a modication on the prototype size

and the runner throat diameter. For the details of exact peak

ef ciency and shape equations and scope of them could see

Gordon's paper [2].

Manness and Doering [4]   developed Gordon's method, with a

large Manitoba Hydro's data. Furthermore, Manness's method

includes the effects of rerunnering turbines in his model while

Gordon's does not. The accuracy of rened model is within  72%

for an older turbine, and within  71% for new one.

3. Design factor affecting turbines ef ciency 

 3.1. Introduction

The majority of the hydraulic turbine manufacturers have

reached a very high level of knowhow which enables them to

carry out hydraulically and structurally correct designed turbines.

So the value of the practically attainable overall turbine ef ciencyη   is mainly inuenced by factors such as surface roughness of 

parts that are in contact with the   ow, and the internal leakageows through the gaps between the blades and shroud. The

former means the performance of a turbine can degrade over

time, due to erosion damage, cavitation damage and weld repairs,

etc. The latter also could get worse due to erosion wear.Fig. 1   shows a breakdown of the loss distribution within a

Francis turbine as a function of specic speed   [5]. The value of 

specic speed directly corresponds to the shape of the runner.

With lower specic speeds, the volumetric losses as well as losses

due to runner disk friction are very signicant. For high head

Francis turbines, the ef ciency due to disk friction can reach up

1.0% [6]. For higher specic speeds, the inuence of blade friction

losses and exit swirl losses in draft tube dominates and mainly

determines the level of the overall ef ciency. There are similar

results for other types of turbines   [3]: turbine ef ciency is a

function of the specic speed, with both low and high specic

speed turbines having lower peak ef ciencies than medium ones.

At lower heads, losses in the draft tube are increasingly signicant;

at high heads,  ow losses through the runner seals increase. Lastly,

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Fig. 1.   Loss breakdown of Francis turbines as a function of speci c speed.

Fig. 2.   Surface roughness impact the Francis turbine specic energy ef ciency.

Fig. 3.   Inuence of buckets erosion on ef ciency of a Pelton turbine.

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larger reaction turbines are more ef cient than smaller ones due

to the relatively lower effect of friction in runners.

 3.2. In uence of surface roughness and wear 

Scientists and engineers have long known that surface rough-

ness on  ow surfaces will rob a moving  uid of energy in piping

systems. Brice and Kirkland   [7]   found the similar relationship

between surface roughness of the turbine components and degra-

dation of the unit performance. Here, the surface roughness

includes the initial roughness strongly depends on the manufac-

turing techniques used, and the roughness which is changed by

wear or erosion. Thereby surface quality causes increased energy

losses during its operation.

The losses are increased by increased roughness due to

increased friction losses usually expressed in the head from theworn surface and an offset from the optimum hydraulic prole.

Friction losses should be special considerable, especially in the

runner where the relative velocity is the greatest. As early as 1978,

Kurokawa et al.   [8]   studied the roughness effects on the three

dimensional boundary layer  ow along an enclosed rotating disk

with theoretical and experimental approaches. And in 1997,

Kubota et al. [9] extracted the specic hydraulic energy deciency

from the performance diagrams of a model turbine changing the

roughness systematically to investigate the effect of surface rough-

ness on a Francis turbine. In 2007, Krishnamachar and Fay [10,11]

synthesized analytical procedures with practical data and pro-

vided a reasonably simple computational method to obtain realis-

tic estimates for roughness effects on the optimum ef ciency of 

Francis turbines. Recently, Maruzewski et al.   [12]   studied thespecic losses per component of a Francis turbine, which were

estimated by CFD simulation. The results were performed for

different water passage surface roughness heights. The IEC (Inter-

national Electrotechnical Commission), IAHR (International Asso-

ciation for Hydraulic Research) and their working groups collected

and analyzed vast data on both model and prototype turbines to

calculate or scale the different friction coef cients by upgrading

the scale effect formulas such as   IEC 60995.

Fig. 2   shows the evolution of the specic hydraulic energy

ef ciency of a Francis turbine versus the sand grain roughness

height and versus the discharge  [12].

The effect due to wear changing the roughness is also sig-

nicant. Truscott [13] surveyed the factors and types of wear, and

the effects of wear on performance and working life. Padhy and

Saini [14] reviewed different causes for the declined performanceand ef ciency of the hydro turbines and suitable remedial mea-

sures suggested by various investigators, based on the literature

survey various aspects related to silt erosion in hydro turbines.

For impulse turbines, wear on needle and nozzle would result

in a decay of ef ciency and possibly cavitation, see Fig. 3 [15]. In

worn bucket, the boundary layer is thickened and disturbed due to

an increased waviness of the surfaces.

For reaction turbines, the performance of a turbine is destined

to degrade due to various reasons as years go by, shown in  Fig. 4

[15]. These factors include metal loss (cavitation, erosion, and

corrosion), opening of runner seal, opening of guide vanes clear-

ances, and increasing surface roughness. Erosive wear due to high

content of abrasive material during monsoon and cavitation is the

very important one [16].

Fig. 4.  Decay of ef ciency due to wear.

Fig. 5.   Blade and casing arrangement in a Kaplan turbine.

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In the presence of particular wear phenomena, mainly threefollowing results will lead to the ef ciency deterioration:

  wear of guide vanes components with increase of clearancebetween guide vanes and wearing plates.

 Surface roughness increases in the runner channels.  Erosion on the seal rings with increase of volumetric losses.

The roughness and wear inuence each other and promote

each other.

 3.3. In uence of gap clearances on the internal leakage

Volumetric losses are mainly caused by the existence of sealing gap

and tip clearance of runners. The higher is the differential pressureacross the space, the greater is the leakage. The leakage   ow

contributes negatively to the turbine performance in several ways.

  Flow loses energy through viscous losses in boundary layer aswell as in viscous mixing with the mainstream.

 Flow does not give work to the blade.  Flow blocks the mainstream by reducing the area available for

the mainstream and increases the 3D turbulent  ow due to the

unsteady leakage vortex.

Worn guide vane end clearances can contribute to a decline in

unit performance. Over years of operation with eroded end

clearances, worn stem journal bushings, and improperly adjusted

toe to heel closures, the leakage through the guide vanes may

double. The tip  ow strengthens the   ow detachment caused bythe strong curvature of the blades and guide vanes. This is very

harmful to the turbine. Since the  ow detachment inuences the

normal guidance made by the guide vanes and blades near their

tips, thus disturbs the   ow at the outlet causing decay of the

energy transformation in the runner, ef ciency losses and local

erosion   [17]. Worse, because of wear, the gap will continually

increase between guide vanes and wearing plates, which produces

an increase of volumetric losses and vortices.

For Kaplan and bulb turbines, since the blades are adjustable,

the runner is not shrouded, there must exist a   nite clearance

between them, shown in Fig. 5. The tip clearance is of the order of 

millimeter, but it is one of the most inuential parts to perfor-

mance of the turbines. These gaps can give rise to leakage  ows,

resulting in the formation of vortices. Based on prototype mea-surements, the leakage loss of a Francis turbine is at about 0.5% to

1%, even if with tight seal gaps [6]. For high head units, leakage by

seal rings may affect the overall ef ciency of the turbine by 1% to

3%   [18]. The vortex breakdown is the cause of the unsteadyow features. These secondary   ows cause elevated water velo-

city, shear and rapid pressure changes and low absolute pressure

levels   [19]. The large pressure gradient between the non-

cavitation pressure side and the cavitation suction side enhances

the tip clearance  ows. Downstream of the trailing edge the  ow

eld is characterized by a strong local   ow blockage in the tip

region. The blockage is extremely large and persistent, and

becomes the dominant single source of hydraulic loss within

the blade passage   [20]. And then tip clearance cavitation takes

place in the gap between the blades and the machine casing. There

Fig. 6.   Inuence of tip clearance ows on the development of cavitation. (a) Numerical result without tip clearence, (b) Numerical result with tip clearence and Experimental

Visualization.

Fig. 7.   Erosion pattern of particles of different diameters in Francis turbine labyrinth.

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could be an erosion risk even though the head could be low, see

Fig. 6 [21].

The effects induced by the presence of the tip clearance do not

have a linear growth with its size. So it is important to determine

the admissible tip clearance size [22]. Okita el al. [21] found the tip

clearance   ows from the pressure side to the suction side of the

blade produced the tip vortex cavitation, which affected the sheet

cavitation on the leading edge of the next blade and enhances the

blockage effect near the casing than the   ows without tipclearance. Nilsson and Davidson   [23]   investigated the turbulent

ow in Kaplan hydraulic turbines. They focused on tip clearance

losses, which reduced the Kaplan turbine ef ciency by about 0.5%.

The computations capture a vortical structure close to the leading

edge tip clearance, where the tip clearance  ow interacts with the

shroud boundary and cavitation occurs. The tip blade loading

increased when the specic speed decreased.

Labyrinth seals are the primary type of seals for hydraulic

turbines, see Fig. 7 [17]. However, as a type of non-contact seal, the

space between the crown and upper cover is   lled with high-

pressure water, which results in a high disk friction loss. Zhao et al.

[24]   carried an experimental study on leakage   ow in different

geometrical disk seals to state that the leakage  ow rate is inverse

proportional to the rotational speed and it could be possible to

optimize disk with tilting pads to reduce the leakage loss.

The hub/tip ratio   ν   is an important parameter as it not only

controls the  ow rate but also inuences the stall conditions, the

tip leakage and the ability of the turbine to run up to operating

speed [25]. Singh and Nestmann [26] concluded that a larger hub/

tip ratio yielded lower runner losses. However, there is no clear

guidance on hub/tip diameter ratio. Without universal formula,

the ratio is determined through a review of empirical methods, e.g.

Nechleba [27], Durali [28] and Wright [29].

 3.4. Others

Hydropower plants often get lots benet from air admission or

air injection  [30–

32], because which smoothes out the annoyinghigh-frequency components of noise and vibration. In addition,

aeration sometimes removes  ow instability by manipulating the

hydraulic transmission behavior   –  in particular lowering the draft

tube natural frequency   [33]. However, few research works have

been published about the effect of   ow aeration on turbine

ef ciency. Energy losses due to aeration increase with the relative

air   ow rate. Parts of results on ef ciency losses due to aeration

have been collected in connection with tests aiming at increased

tail water oxygen content   [34–36].   Depending on design, it is

necessary to add inserts in the draft tube. These structures

obstruct the   ow and cause additional drop in ef ciency. Such

additional loss may be avoided if air can be admitted through the

shaft bore or head cover [33].

 3.5. Discussion

The presented results show that disk and gap losses play a big

part in low specic speeds. So there is the highest potential for an

ef ciency improvement in the region of low specic speeds. All

efforts aimed at an improvement of the surface quality and wear

protection of wet surface of components will cause a gain of 

ef ciency. Furthermore, it is worthy to reduce the clearance of the

sealing gaps to the smallest possible value in order to decrease the

volumetric losses.

It is mentioned that the conditions of the surfaces as well as the

sealing gaps will decay by the time of operation. So it makes sense

to check these parameters at reasonable intervals during the

lifetime of a turbine.

4. Performance testing 

CFD methods, talked about in next section, provide the turbine

designer with powerful tools for achieving highly ef cient hydraulic

turbine designs. However, CFD techniques cannot be in accordance

with the true nature very well, especially in complex physic

environment. CFD methods still require   ne-tuning with test

results. Turbine performance test parameters typically include:

generator output, turbine  ow rate, headwater and tailwater eleva-tions, inlet head and discharge head. There are two kinds of tests in

hydraulic turbines, one is model test and the other is  eld test.

4.1. Model tests

Model test is an important element in the design and devel-

opment phases of a new turbine. It will verify the performance of a

given turbine design. It is necessary for determining performance

over a range of operating and for determining quasi-transitory

characteristics. Model test can also be used to eliminate or

mitigate problems associated with cavitation, hydraulic thrust,

vibration and pressure pulsation. A standard for model testing of 

water turbines is  International Standard IEC-60193. In general  IEC-

60193   applies to any type of reaction or impulse turbine testedunder prescribed laboratory conditions and may accordingly be

used for acceptance tests of the prototype turbines as well. Typical

laboratory facilities include [37]:

 Water tunnels;   Depressurized  umes;  Depressurized towing tanks;   Pump and turbine test loops;  Other test apparatus, i.e. cavitation erosion test.

The formula for up scaling the ef ciency form the model to the

prototype Francis turbine is:

Δη¼   1 ηm

V   1   Rem=R

ep α    ð2Þ

whereΔη is the rated ef ciency difference between the prototype

and the model,   ηm   is the ef ciency of the model,   Rem,   Rep   is the

Reynolds numbers of the model and prototype respectively,  V   is

the scalable part of the losses, and   α   is exponent. For Kaplan

turbines, the value of  V   is different.

There is a debate in the extrapolation of model test results to

prototype values. In principle, based on the similarity laws, various

scaling formulas can be used to estimate prototype values (i.e.

discharge, speed, power, etc.) from model tests. In fact, too many

factors can lead to the prototype real value different from those

calculated by scaling formulas. The essential reason is that all of 

losses lead to ef ciency will change in prototype machine. Oster-

walder and Hippe   [38]   made attempts to set out diagrams

permitting a quick determination of ef ciency scaling. Bachmannel al.   [39]   proposed some methods to predict the prototype

ef ciencies. The   IEC-60913   thought losses could be classied into

two categories based on whether those losses depended on

Reynolds number. For reaction turbines, friction losses are mainly

dependent on the Reynolds number provided that  ow conditions

are hydraulically smooth. Because the Reynolds number of the

model, referred to the reference diameter of the machine (or to a

characteristic length of a component), is usually smaller than that

of the prototype, the ratio of friction losses to total losses for the

model becomes larger than the corresponding ratio for the

prototype. Therefore, in most cases, model ef ciency is somewhat

lower than prototype ef ciency. Because of two-phase  ow in the

turbine housing, the ef ciency of impulse turbines (e.g. Pelton

type) may be strongly inuenced by the Froude number.

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Therefore,   IEC-60913   recommends, for impulse turbine model

tests, to choose a specic hydraulic energy which satises the

Froude similitude. Standard   JSME   ( Japanese Society of Mechanical

Engineers) S008 also summarized the viscous losses [40]. It thought

loss distribution factor was function of the specic speed, while it

was constant in the  IEC-60193  for each type of machine.

The unsteadiness, not mentioned by various standards, exactly

makes different contributions on losses. Actually, this is a very

important feature because a  ow must be unsteady in so complexpassages. Research in EPFL (Ecole Polytechnique Federale de

Lausanne) group conrmed that   ow unsteadiness disturbed the

boundary layer in Francis turbines [41,42]. Li  [43] in his PhD thesis

did an experimental investigation of head loss of oscillatory  ow

in a rectangular. The head losses increase with the amplitude of 

the oscillation and the frequency, which means   ow unsteadies

may also lead to additional viscous losses in turbulent   ows. So

when and how the scaling formulas take these losses into account

need more research.

4.2. Field tests

The previous section has told a truth that though a good result

got in model test, there is no guarantee that the prototypemachine is an accurate reproduction of design. Besides,   ow

conditions, intake head losses, water quality, the effect of operat-

ing other adjacent units, etc., cannot be analyzed in model tests.

For these reasons,  eld performance tests will often be performed

once prototype machine is installed. Field tests are also performed

for commission a site and for various problem-solving activities.

However,   eld tests also cannot take the place of model tests.

Some conditions, such as severe cavitation and maximum run-

away speed, can be simulated in model tests, but seldom tested in

a prototype. The factors leading to difference between model test

results and   eld test results include: ef ciency step up, power-

house head determination, site differences, manufacturing differ-

ences, deection differences and wear [44].  International Standard

IEC-60041   and   ASME PTC 18-2011  describe the basic procedures

and code-accepted measurement methods.

There are several different types of   eld tests which serve

different purpose: the absolute ef ciency and the relative ef -

ciency. The former is measured for acceptance or performance

tests, more complex, more expensive, commonly tested once;

while the latter is measured when operating information or  ne-

tuning of turbine performance is desired. The difference is

whether the discharge is measured absolutely or in relation to

some other known parameters.

The absolute methods include: the velocity–area method by

means of current-meters or Pitot tubes, the pressure–time method

(Gibson method), tracer methods either by transit-time or dilution

measurement, standardized thin-plate weirs, standardized differ-

ential pressure devices, and volumetric gauging. In addition the

acoustic method also is optional. Moreover, the thermodynamicmethod of ef ciency measurement permits discharge to be

obtained as a derived quantity from ef ciency, specic energy

and power measurements.

Relative methods such as the Winter–Kennedy method, non-

standardized differential pressure devices, non-standardized weirs

or   umes, certain simple forms of the acoustic method or local

velocity measurement with a single current-meter may be used to

obtain a relative value of the discharge or even an absolute value if 

they are calibrated in situ by comparison with an absolute method.

4.3. Discussion

Usually the performance of large turbines is determined  rst in

model tests. However prototype turbine installations always have

some differences from their model, which alter their performance.

No matter model or   eld tests, the core problem is to develop a

high accuracy method to ascertain performance by measuring ow

rate, head, and power, from which ef ciency may be determined. A

major dif culty resides in the accurate determination of the  ow

rate. Work should be concentrated methods of measurement,

testing procedures, and methods of calculation. Another problem

is to develop high accuracy correction and extrapolation princi-

ples. Every reasonable effort shall be made to conduct the test asclose as possible to specied operating conditions in order to

minimize deviation corrections. And the study of the various

models of the energy conversion associated with all kinds of 

losses is help to reduce the extrapolation deviation.

5. CFD method for promoting the research and design

The   ows in turbine system are almost invariably turbulent.

The development and interaction of boundary layers and separa-

tion of boundary layers cannot be completely analyzed theoreti-

cally. To predict the behavior of   uids in turbulent   ow,

computational   uid dynamics (CFD) based on turbulent models

of  uid behavior can provide better visual solutions of  ows and

valuable data. The design calculations for attaining the highest

possible ef ciency and the optimization are done on a computer

with CAD and CFD approaches. Expect for design stage, before

upgrading or rehabilitation, tests are carried out to determine the

ef ciency to reveal that the current ef ciency of the turbine is

indeed lower than expected. This is necessary to refurbish the

units. However there is no way to verify if the new turbine meets

the performance improvement before which is really manufac-

tured. Nowadays, with CFD technology, engineers are able to

simulate the new one at required operating zone, including theow as the water passes through the intake, penstock, spiral

casing, stay/guide vanes, the runner and draft tube. With CFD,

plants and manufactures can save large money from the expensive

tests and lots of physical modications. From last few decades, the

vast number of applications by the CFD method in engineering hasproven this approach is an important help to designers and

operators. Even then, models must still be designed and tested

before a prototype machine can be built.

5.1. Improving pressure recovery in draft tube

The numerical   ow simulation in draft tube is one of most

dif cult and least reliable. Workshops [45,46], such as Turbine 99,

validated the computational method and parameters, and exam-

ined the accuracy of draft tube   ow prediction. The Swiss EPFL 

[47] continued the research on the draft tube   ow analysis. They

compared the measurement data of the pressure recovery of the

model of FLINDT Francis turbine with CFD predictions of all

different FLINDT partners. After few years' effort, the predictionof the pressure recovery with the CFD approach seems reliable

under clean and precise modeling only. Pan   [48]   simulated a

hydro-turbine system provided by Waterpumps Oy, Finland. With

the CFD method, they found the turbine system ef ciency is

increased by 1.5% and the draft tube pressure recovery factor is

increased by 4.03%, by introducing Vortex Generators into the

draft tube.

Up to now, CFD prediction of draft tube   ow is still an

open issue.

5.2. Cavitation research by CFD

Turbines show declined performance after few years of opera-

tion, as they get severely damaged due to various reasons. One of 

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the important reasons is erosive wear of the turbines due to

cavitation. Reaction turbines, however are more prone to cavita-

tion especially Francis turbines where a zone in the operating

range is seriously affected by cavitation and considered as for-

bidden zone. Cavitation is a phenomenon which manifests itself in

the pitting of the metallic surfaces of turbine parts because of the

formation of cavities   [49]. Few years ago, the CFD method

generally identies cavitation risk by evaluating zones of pressure

below vapor pressure in computed  ow elds with a single-phasemodel. Its major disadvantage is that the effect of a cavitation

bubble on the   ow   eld is neglected. Perhaps this approach is

adequate in most cases. But it cannot provide more information

such as the effect of cavitation on the ef ciency or a more accurate

prediction of the extent of a cavitation bubble. The CFD method in

two-phase simulation has to be carried out. The most powerful

model is the Rayleigh–Plesset two-phase   ow model. This

approach is being used for modeling the formation and decay of 

vapor bubbles. So it can enable a more accurate prediction of the

cavitation zone and the associated drop in ef ciency. Wu et al. [50]

simulated the unsteady cavitation turbulent   ow in a Francis

turbine using the RANS method and the improved mixture model

of two-phase   ows. Necker and Aschenbrenner   [51]   calculated a

two-phase   ow including cavitation model in a horizontal shaft

bulb turbine, and Szantyr et al.   [52]   analyzed the tip vortex

cavitation with experimental and numerical methods. All of their

work got good results in validation of the CFD approach compared

with the experimental data. The predicted size and position of the

vapor zone is found to be in very good agreement with the

observation. There is still more work needed in the prediction of 

the related rise and sharp drop in ef ciency with decreasing the

Thoma number  [53]. Kumar and Saini   [49]  gave a very compre-

hensive and systemic review on cavitation in hydro turbines.

5.3. CFD in tip clearance

Flow simulation in tip clearance needs a   ner grid scheme in

the boundary layer. Sell  [20] simulated the tip clearance affect on

the  ow  eld in a turbine blade row. The static pressure distribu-

tion indicated that care had to be taken in the selection of 

appropriate downstream boundary conditions for the computation

of the unusual  ow features. Liao et al.  [54] analyzed the internal

ow in a Kaplan turbine runner with the Triangle Acute Clearance.

Control of the leakage  ow by modifying the blade tip shape has

been the main subject for much research [55]. Actually cavitation

easily occurs in the tip clearance, so two-phase cavitation model

should be taken into account in the CFD approach. Okita et al.  [21]

numerically analyzed the inuence of the tip clearance   ows on

the unsteady cavitation   ows in the 3D inducer. Because of 

cavitation feature and boundary layer effect, further research is

needed.

5.4. Prediction of erosion in hydraulic turbines

State of the art CFD methods are employed to further under-

stand the mechanics of hydro-abrasive erosion and, in particular,

to design erosion-resistant hydraulic proles [56]. At present, the

computerized methods successfully predict the region of max-

imum wear and can somewhat mitigate the erosion by rening

hydraulic design and exact type and position of protective coatings

needed [57].

5.5. CFD in off-design

Boundary layer separation can be negligible when a turbine is

operating near its design point, and the dominant  ow character-

istics in the   ow passages can be calculated by CFD. These

calculations can lead to new runner design having signicantly

higher ef ciencies than older designs. However, one of the most

challenges for CFD is that off-design  ow characteristics cannot be

calculated with condence. Since boundary layer separation

occurs and leads to highly complex   ow patterns that defy

accurate description.

The   ow at the draft tube inlet is characterized by a strong

swirl in a certain range of off-design operation. This is a very

popular focus on CFD simulation in off-design. The strong pressurepulsations and rotating vortex can even damage the draft tube and

make a sharply drop in ef ciency. Paik et al.   [58]   calculated

incompressible swirling ow in a typical hydroturbine draft tube

unsteady Reynolds-averaged Navier–Stokes (URANS) simulations

and detached-eddy simulations (DESs). Their method could cap-

ture the onset of complex, large-scale instabilities in the   ow,

including the formation of a precessing spiral rope vortex, and

yield mean velocity proles in reasonable agreement with mea-

surements, and Stein et al. [59] found that the CFD simulation of 

the draft tube requires great care with respect to turbulence

model. Because of the strongly curved   ow paths and invalid of 

the assumption of isotropy, the Reynolds stress models, Large Eddy

Simulation or similar approaches should be applied instead of 

two-equation turbulent models. Draft tube vortex simulation with

a two-phase approach using the Rayleigh–Plesset model, which

require huge computational grids for an accurate simulation, is a

serious challenge. Here too, more work is needed.

5.6. Discussion

Using CFD simulation provides not only better energy conver-

sion ef ciency by improved shape of turbine runners and guide/

stay vanes, but also leads to a decrease in cavitation damages at

high head plants and reduced abrasion effects when dealing with

heavy sediment-loaded propulsion water. So in hydraulic turbine

eld, CFD is becoming a powerful tool, but requires validation

versus smartly designed and executed experiments as well as

profound knowledge in   uid mechanics. CFD is good, but not

excellent enough. There is a lot work needed, in particular the off-

design simulation.

6. Ef ciency improvement in turbines

Large turbines are close to the theoretical ef ciency limit when

operated at the best design point. But this is not always possible.

Further and continued research is needed to make more ef cient

operation possible over a broader range of  ows. At the same time,

most of the existing units will need to be modernized during the

next three decades, allowing for improved ef ciency and higher

power and energy output by retrotting new equipment. CFD is an

important tool, making it possible to design turbines with high

ef ciency over a broad range of discharges. Improving operationand reducing the cost of maintenance of equipment by new

techniques (e.g. articial intelligence, neural networks, fuzzy logic

and genetic algorithms) is also an innovational approach   [57].

Generally speaking, based on the actual problem, there are two

types of approaches to improve the hydraulic turbine's ef ciency,

better structural design or optimization and surface improvement.

6.1. Better design or optimization

Through experimental and numerical data accumulated, opti-

mizing the hydraulic performance of turbine components is more

and more easy and automatic. There is a great technique and

market potential for units modernization. Since the older ones

were not optimum design within the limitations of their

 X. Liu et al. / Renewable and Sustainable Energy Reviews 51 (2015) 18– 28   25

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contemporary technology. Replacement of stator and/or rotor

proled machinery parts with new ones can increase the ef -

ciency. For example, just minor modications to the stay/guide

vane system could result in operation ef ciency which increases to

0.5% or more. These optimizations are easily studied in a CFD

model and/or physical model. The blade proles rening, even a

partial renewal, can increase much more ef ciency than other

components modication. More twisted blade in 3D space, such as

X-type blade for Francis turbines, in some cases can improve over5 percent points than the very old units. Tip leakage cannot be

avoided. The technique that tends to reduce the tip leakage losses

has the objective to decrease the tip gap mass  ow rate. A detailed

review of the various aspects of axial turbine tip clearance leakageow is given by the  VKI Lecture Series 2004-02  [60]. Reducing the

negative effects of the tip leakage is generally referred to as tip

desensitization. The desensitization methods include active and

passive methods   [55]. The latter is the major form in hydraulic

turbines. The passive control is simple, practical, and effective,

through modifying the blade/tip shape to control the leakage  ow.

These blade tip geometries are squealer tips and winglets or tip

chamfering.

6.2. Improve the surface performance

Grinding, coating or painting the wet surfaces can rene the

roughness and improve the wear resistance in surface. And it is

also good to maintain and extend life of these structures.

Reducing the surface roughness of the penstock interior (i.e.

minimize frictional resistance) will help reduce the head loss

through the system, by using new coating materials. Some new

technology coating, such as silicone-based fouling release systems,

not only improve surface roughness but also can limit organic

buildup   [61,62]. And another method is taking the innovative

containment principles and permeability control measures in pipe

design and construction to minimize water leakage through the

rock mass. CFD technology yields more accurate penstock hydrau-

lic designs for hydrodynamic loading limiting head loss and

reducing water hammer effects. Paish et al. [63], Maher and Smith

[64], Alexander and Giddens  [65]  provided in depth guidance on

optimizing the penstock design for hydro systems.

For Pelton turbines, in order to keep the performance, suf cient

the coating of needles and nozzles is relatively inexpensive and

helpful for preserving the quality and the compactness of the jet.

For Francis turbines, the conditions of component are quite more

complex than Pelton. Coating of stationary/rotating seal rings,

guide vanes including their wearing plates, and inlet and outlet

edges of the runner can keep turbine in good performance. In

some cases,  eld tests found that ef ciency may improve 0.1% to

0.8% comparing pre-coated versus post-coated performance  [66].

Applying the new materials is another useful way to improve

the surface performance. Use suitable proven materials such as

stainless steel and the invention of new materials for coatings tomanufacture the components of turbines to maximize the resis-

tance to erosion, abrasive wear and cavitation, and to extend

lifespan. If the sediments contain hard minerals like quartz, the

abrasive erosion of guide vanes, runners and other steel parts may

become very high and quickly reduce ef ciency or destroy

turbines completely within a very short time  [56]. New solutions

are being developed by coating steel surfaces with a very hard

ceramic coating, protecting against erosive wear or delaying the

process.

6.3. Improvements to hydropower production

High-ef ciency or cost-effective operation requires attention to

both the individual turbine performance and the entire system

characteristic. Sometimes engineers pay more attention to the

instant demands of the turbine. As the supplementary introduc-

tion of the ef ciency improvements of turbines, ways to increase

the value of hydropower were discussed here briey.

Compared to fossil, nuclear, wind, and other renewable ener-

gies, hydropower resources have the   exibility and cost advan-

tages. But that does not mean hydropower is immune to

restrictions on operation. Attempting to maximize prot to safe-

guard the future of the facility, hydropower facilities must satisfy anumber of environmental and operational constraints. Some of 

these constraints on hydropower operations include: [67]  “(1) lim-

itations in maximum and minimum water output which can vary

by season, time of day, abnormal events such as   ooding and

drought, and environmental and regulatory policies; (2) facility

restrictions such as the vibration of equipment as turbines ramp

up and ramp down, optimizing ef ciency to ensure maximum

return of investment, and minimum and maximum generator

production limits; and (3) electrical considerations such as over

voltage and under voltage conditions and market prices that

ensure that the hydro facility is still protable”. For more details

on the specic water constraints experienced at hydro facilities,

please refer to the Oak Ridge National Laboratory report from 2012

[67].

From the Energy Department, the Electric Power Research

Institute's (EPRI) report   [68], outlining key improvements can

provide more ef cient and cost-effective electricity to homes and

business in the United States. Efforts during this study have

addressed operational, market, business, and policy considerations

in valuing hydropower. A compact and simple review of this report

and the original version can be found on the website of U.S.

department of energy. This report identies and assesses the

quantiable benets from potential improvements, such as instal-

ling turbines that can operate with lower water levels, utilizing

new power plant designs that can increase revenue and ef ciency.

This study looked at improvements that could boost the ef ciency

and output of hydropower plants. By deploying new hydropower

technologies, making operational improvements, utilizing hydro-

power's  exibility more in grid resource planning, and monetizingthe energy storage capability of pumped storage, hydropower

plants could reach their largest revenue and ef ciency increases.

Here are some key  ndings from the report [68]:   “(1) relying more

heavily on hydropower to address changes in electricity supply

and demand could provide more   exible reserve power options

and reduce wear and tear on conventional thermal-generating

equipment; this could translate to a 40% increase in the total

annual value of hydropower. (2) Expanding the effective operating

range of hydropower units—by reducing the minimum amount of 

water needed to use the turbines stably—can increase the produc-

tion value of plants by 60%. (3) Designing and implementing

cutting-edge plant designs that allow pumped storage to provide

grid services while pumping water would result in an 85% increase

in production value. (4) Treating pumped storage units as a unique“asset class”   would allow the creation of alternative business

models that could make investment in pumped storage more

attractive by integrating with variable renewables.”

7. Conclusion

Ef ciency, reliability, and maintenance of hydraulic turbines are

most important for the economy and safety of hydropower.

However, basic knowledge of design and maintenance is required

to select the best equipment for a safe operation with highest

possible production. This paper reviewed a set of empirical

equations replaced of full database which is almost impossible to

get from different manufactures. It denes the peak ef ciency and

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shape of the ef ciency curve as a function of the commissioning

date for the unit, rated head, rated   ow and other main design

parameters. The informed selection and use of turbines can benet

from the application of these equations.

The presented results show that disk and gap losses play a big

part in low specic speeds. So there is the highest potential for an

ef ciency improvement in the region of low specic speeds.

Furthermore, it is worthy to reduce the clearance of the sealing

gaps to the smallest possible value in order to decrease thevolumetric losses.

Testing and CFD are the most two important tools in different

design stages. Work should be concentrated methods of measure-

ment, testing procedures, and methods of calculation. Another

problem is to develop high accuracy correction and extrapolation

principles to specied operating conditions in order to minimize

deviation corrections. Modern CFD  ow analysis, FEA for engineer-

ing in manufacturing have signicantly improved turbine ef -

ciency and production accuracy. The next step is to improve

turbine performance at off-design heads/discharges and to

improve range of operating heads/discharges. With the help of 

the test validation, fast, well-calibrated CFD methods for design

will be automatized to a higher degree, and improve the off-design

operation simulation accuracy.

Now the peak ef ciency of turbines based on hydraulic design

is almost reaching the theoretical limit. Optimization of the

hydropower systems considering various factors will make more

promising than purely optimization of structures. In future, opti-

mization of operation, mitigating or reducing environmental

impacts, adapting to new social and environmental requirements

and more robust and cost-effective technological solutions are

more and more important. Such as variable-speed turbines, matrix

technology,   sh-friendly turbines (e.g. Alden Turbine), hydroki-

netic turbines, or hybrid wind–hydropower turbine systems, etc.

with the application of new technologies, the new styles of 

turbines are more ef cient and environmentally friendly, and

can compete with traditional designs.

 Acknowledgments

The   rst author is grateful to the China Scholarship Council

(CSC) for  nancial support to study in University of Toronto. And

this work was supported by National Natural Science Foundation

of China, China (No. 51279083).

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