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NUMERICAL MODELLING OF HORIZONTAL AXIS
TIDAL TURBINE WITH VARIABLE LENGTH BLADE
FARHANA ARZU
DEPARTMENT OF CIVIL ENGINEERING
FACULTY OF ENGINEERING
UNIVERSITY OF MALAYA
KUALA LUMPUR
2018
NUMERICAL MODELLING OF HORIZONTAL AXIS TIDAL TURBINE WITH VARIABLE LENGTH BLADE
FARHANA ARZU
THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER
OF ENGINEERING SCIENCE
DEPARTMENT OF CIVIL ENGINEERING FACULTY OF ENGINEERING UNIVERSITY OF MALAYA
KUALA LUMPUR
2018
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UNIVERSITY OF MALAYA
ORIGINAL LITERARY WORK DECLARATION
Name of Candidate: Farhana Arzu (Passport No: )
Matric No: KGA 140019
Name of Degree: Master of Engineering Science
Title of Thesis: NUMERICAL MODELLING OF HORIZONTAL AXIS TIDAL
TURBINE WITH VARIABLE LENGTH BLADE
Field of Study: Water Resource Engineering
I do solemnly and sincerely declare that:
(1) I am the sole author/writer of this Work; (2) This Work is original; (3) Any use of any work in which copyright exists was done by way of fair dealing
and for permitted purposes and any excerpt or extract from, or reference to or reproduction of any copyright work has been disclosed expressly and sufficiently and the title of the Work and its authorship have been acknowledged in this Work;
(4) I do not have any actual knowledge nor do I ought reasonably to know that the making of this work constitutes an infringement of any copyright work;
(5) I hereby assign all and every rights in the copyright to this Work to the University of Malaya (“UM”), who henceforth shall be owner of the copyright in this Work and that any reproduction or use in any form or by any means whatsoever is prohibited without the written consent of UM having been first had and obtained;
(6) I am fully aware that if in the course of making this Work I have infringed any copyright whether intentionally or otherwise, I may be subject to legal action or any other action as may be determined by UM.
Candidate’s Signature Date:
Subscribed and solemnly declared before,
Witness’s Signature Date:
Name:
Designation:
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NUMERICAL MODELLING OF HORIZONTAL AXIS TIDAL TURBIN E
WITH VARIABLE LENGTH BLADE
ABSTRACT
Marine renewable energy is one of the major alternative sources of energy to meet the
current energy demand. Rotor blades have the main influence on the efficiency of tidal
turbines. The variable length blade technology has already been used in designing wind
turbine blades for efficient energy extraction. The movable tip blade section of variable
blade length turbine offers full control on performance characteristics and power capture,
but has limited application in marine field. In this study, a variable length blade horizontal
axis tidal turbine (HATT) model is studied numerically to investigate the hydrodynamic
performance and power output. A new open source software package QBlade 0.8 and
ANSYS FLUENT 15.0 were used for two-dimensional BEMT (blade element
momentum theory) and three-dimensional CFD (computational fluid dynamics)
simulations respectively. Both the simulation techniques have been validated against the
available published data of the HATT models. The effect of different tip blade extensions
on the non-dimensional performance parameters (power, thrust and moment coefficient)
and power output of the rotor model were studied at rated and below-rated conditions of
the model. The performance data then were compared with the standard fixed length blade
tidal turbine. Non-dimensional performance coefficients were observed to improve with
the increment of rotor diameter at high TSRs. Peak power coefficient value was dropped
by 9% when the blades extend from 10% to 40%. On the other hand, power extraction
was enhanced up to 72% at below-rated tidal velocities without any loss in performance
at rated condition. The model is found to be more efficient compared with the
conventional tidal turbine models and thus recommended as a good candidate to replace
the other conventional HATTs.
Keywords: variable length blade, numerical simulation, performance, power.
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MODEL NUMERIKAL TURBIN SUDUT MELINTANG PASANG SURUT DENGAN BILAH LENGAN BELAS
ABSTRAK
Tenaga boleh diperbaharui marin merupakan salah satu sumber utama tenaga
alternatif untuk memenuhi permintaan tenaga semasa. Bilah pemutar mempunyai
pengaruh utama ke atas kecekapan turbin pasang surut. Teknologi bilah panjang boleh
laras telah digunakan dalam merangka bilah turbin angin untuk pengekstrakan tenaga
dengan lebih cekap. Bahagian bilah hujung bergerak dari turbin panjang bilah boleh laras
menawarkan kawalan penuh ke atas prestasi dan penjanaan kuasa, tetapi mempunyai
aplikasi yang terhad dalam bidang marin. Dalam kajian ini, panjang paksi pemboleh ubah
model turbin pasang surut (HATT) dikaji secara berperingkat untuk mengkaji prestasi
hidrodinamik dan penjanaan kuasa. Dengan menggunakan perisian dari sumber terbuka
iaitu QBlade 0.8 dan ANSYS FLUENT 15.0 digunakan untuk BEMT dua dimensi (teori
momentum unsur bilah) dan simulasi CFD tiga dimensi. Kedua-dua teknik simulasi ini
telah disahkan dengan data yang dipaparkan dari model HATT. Kesan pelanjutan bilah
hujung yang berlainan pada parameter prestasi tidak berdimensi (kuasa, tujahan dan
pekali momen) dan penjanan kuasa model pemutar telah dikaji pada syarat-syarat yang
dinilai dan di bawah model ini. Data prestasi kemudian dibandingkan dengan turbin
standard pasang surut yang mempunyai panjang yang tetap. Pekali prestasi bukan dimensi
diperhatikan dengan peningkatan diameter pemutar di TSR tinggi. Nilai pekali kuasa
puncak dikurangkan sehingga 9% apabila bilah-bilah memanjang dari 10% hingga 40%.
Sebaliknya, penjanaan kuasa dipertingkatkan sehingga 72% pada halaju pasang surut
rendah tanpa sebarang kehilangan prestasi. Model ini didapati lebih cekap berbanding
model turbin pasang konvensional dan dicadangkan untuk menggantikan HATT
konvensional yang lain.
Kata kunci : panjang bilah boleh laras, simulasi numerikal, prestasi, kuasa.
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ACKNOWLEDGEMENTS
The author would like to take the opportunity to express her heartiest gratitude to her
supervisor Dato’ Prof. Ir. Dr. Roslan Bin Hashim for his time, support, inspiration and
expertise throughout this research. This report would not be possible without his critical
comments, guidance and encouragement at various stages of research. The author is
indebted to him forever.
The most sincere appreciation goes to University of Malaya (UM), Kuala Lumpur,
Malaysia for supporting financially through High Impact Research Grant (H-16001-00-
D000047) and for excellent working environment for this research. The author also would
like to thank all the members in the department of Civil Engineering, University of
Malaya for their cooperation. She wishes them all to accomplish their goals successfully.
Finally, the author is thankful to her family and all those who cooperated and expressed
best wishes for her; appropriate words could not be found to express gratitude to all the
well-wishers.
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TABLE OF CONTENTS
ABSTRACT ..................................................................................................................... iii
ABSTRAK ...................................................................................................................... iiv
Acknowledgements ........................................................................................................... v
Table of Contents ............................................................................................................. vi
List of Figures .................................................................................................................. ix
List of Tables.................................................................................................................... xi
List of Symbols and Abbreviations ................................................................................. xii
CHAPTER 1: INTRODUCTION .................................................................................. 1
1.1 Research background ............................................................................................... 1
1.2 Present status of renewable energy in Malaysia ...................................................... 3
1.3 Problem statement ................................................................................................... 4
1.4 Aim and objectives of the study .............................................................................. 6
1.5 Scope of the study .................................................................................................... 7
1.6 Outline of the dissertation ........................................................................................ 8
CHAPTER 2: LITERATURE REVIEW ...................................................................... 9
Tidal energy extraction devices ............................................................................... 9
Horizontal axis tidal turbines (HATTs) .................................................... 10
Vertical axis tidal turbines ........................................................................ 12
Alternative turbines .................................................................................. 13
Securing, installation and maintenance ................................................................. 15
Turbine blade design considerations ..................................................................... 16
Turbine blade performance .................................................................................... 18
Power and mechanical load control systems ......................................................... 19
vii
Variable length Blade control system ...................................................... 21
Two-dimensional foil performance ....................................................................... 23
Blade element momentum theory .......................................................................... 25
Momentum theory .................................................................................... 26
Blade element theory ................................................................................ 30
Blade element momentum equations ....................................................... 33
Computational fluid dynamics (CFD) ................................................................... 35
RANS viscous models .............................................................................. 38
Summary ................................................................................................................ 40
CHAPTER 3: METHODOLOGY ............................................................................... 41
Variable length blade HATT modelling ................................................................ 42
Two-dimensional (2D) BEMT simulation............................................................. 45
Hydrofoil analysis .................................................................................... 46
Rotor model generation ............................................................................ 46
Blade element momentum analysis .......................................................... 47
QBlade BEMT code validation ................................................................ 47
Three-dimensional CFD investigation method ...................................................... 48
Geometry preparation ............................................................................... 48
Mesh generation ....................................................................................... 51
CFD solver setting .................................................................................... 52
Post processing (calculation of performance coefficients and power) ..... 54
Mesh selection .......................................................................................... 54
Time step selection ................................................................................... 55
CFD FLUENT model validation .............................................................. 56
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CHAPTER 4: RESULTS AND DISCUSSION .......................................................... 57
4.1 Validation of the simulation techniques ................................................................ 57
4.1.1 Validation results of QBlade simulation tool ........................................... 57
4.1.2 Validation results of CFD simulation tool ............................................... 63
4.2 Non dimensional performance characteristics of HATT model ............................ 63
4.2.1 Performance coefficients prediction from BEMT study .......................... 64
4.2.2 Performance coefficients prediction from CFD study.............................. 68
4.3 Power extraction .................................................................................................... 70
4.3.1 Power prediction from BEMT analysis .................................................... 71
4.3.2 Power prediction from CFD analysis ....................................................... 72
CHAPTER 5: CONCLUSIONS & RECOMMENDATIONS FOR FUTURE
WORK…………. ........................................................................................................... 74
5.1 Summary of the work ............................................................................................ 74
5.2 Conclusions ........................................................................................................... 75
5.3 Recommendations for future work ........................................................................ 76
References ....................................................................................................................... 77
List of Publications and Papers Presented ...................................................................... 84
ix
LIST OF FIGURES
Figure 2.1: SeaGen device developed by Marine Current Turbine (MCT) .................... 10
Figure 2.2: Examples of horizontal axis tidal turbines ................................................... 11
Figure 2.3: Vertical axis tidal turbines ............................................................................ 13
Figure 2.4: Examples of major alternative turbines ........................................................ 15
Figure 2.5: Different control systems affecting blade performance ............................... 20
Figure 2.6: Variable length blade turbine concept .......................................................... 23
Figure 2.7: Foil orientation ............................................................................................. 24
Figure 2.8: Blade element momentum analysis of HATT .............................................. 26
Figure 2.9: Single stream tube analysis........................................................................... 27
Figure 2.10: Rotating annular stream tube ...................................................................... 28
Figure 3.1: Flow chart of the research methodology ...................................................... 41
Figure 3.2: Baseline model tidal turbine blade profile .................................................... 42
Figure 3.3: Variable length blade HATT model ............................................................. 44
Figure 3.4: Blade profile of model HATT ...................................................................... 45
Figure 3.5: 3D turbine rotor geometry ............................................................................ 49
Figure 3.6: Turbine geometry surrounded by sub-domain and main domain ................. 50
Figure 3.7: Meshing of blade surface, rotor and main domain ....................................... 51
Figure 4.1 Power coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 0º) ................................................................................................................. 58
Figure 4.2 Power coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 5º) ................................................................................................................. 58
Figure 4.3: Power coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 10º) ............................................................................................................... 59
Figure 4.4: Thrust coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 0º) ................................................................................................................. 59
x
Figure 4.5: Thrust coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 5º) ................................................................................................................. 60
Figure 4.6: Axial thrust coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 10º) ..................................................................................................... 60
Figure 4.7: Power coefficient data comparison for QBlade BEMT code validation (Case 2) ..................................................................................................................................... 61
Figure 4.8: Power coefficient data comparison for QBlade BEMT code validation (Case 3) ..................................................................................................................................... 61
Figure 4.9: Power coefficient data comparison for CFD technique validation............... 63
Figure 4.10: Lift coefficient vs angle of attack for NACA-63418 hydrofoil .................. 64
Figure 4.11: Drag coefficient vs angle of attack for NACA-63418 hydrofoil ................ 65
Figure 4.12: Power coefficient (CP) vs. TSR with different tip blade extensions .......... 66
Figure 4.13: Torque coefficient (CM) vs. TSR with different tip blade extensions ........ 67
Figure 4.14: Axial thrust coefficient (Ct) vs. TSR with different tip blade extensions .. 68
Figure 4.15: Performance coefficient curves of 10% extended blades from CFD analysis ......................................................................................................................................... 69
Figure 4.16: Performance coefficient curves of 40% extended blades from CFD analysis ......................................................................................................................................... 70
Figure 4.17: Effect of blade extensions on power output ............................................... 71
Figure 4.18: Power output for minimum and maximum extended model ...................... 72
xi
LIST OF TABLES
Table 3.1: Particulars of the tidal turbines for QBlade BEMT code verification ........... 47
Table 3.2: Cases considered in CFD simulation ............................................................. 48
Table 3.3: Important solver settings for CFD simulation ............................................... 53
Table 3.4: Mesh dependent peak CP checks for maximum extended model .................. 55
Table 3.5: Time dependent peak CP checks for maximum extended model ................... 56
Table 4.1: Comparison of hydrodynamic performance data among different investigations ......................................................................................................................................... 62
Table 4.2: Comparison of power capture at different tide speeds ................................... 73
xii
LIST OF SYMBOLS AND ABBREVIATIONS
A : Rotor area, m2
a : Axial induction factor
a’ : Tangential induction factor
B : Number of blades
D : Rotor diameter, m
�� : Power coefficient
�� : Thrust coefficient
�� : Torque coefficient
�� : Drag coefficient
�� : Lift coefficient
�� : Moment coefficient
�� : Normal load coefficient
� : Tangential load coefficient
c : Chord length, m
dL : Sectional lift force, N
dD : Sectional drag force, N
dm : Sectional moment
dT : Sectional thrust force, N
dM : Sectional torque, N-m2
F : Total loss factor
FN : Normal load, N
FT : Tangential load, N
Ftip : Tip loss factor
Fhub : Hub loss factor
K : Turbulent kinetic energy, m2/s2
M : Torque, N-m2
N : Rotor rotational speed, rpm
xiii
Ne : Ensemble average of experiments
n : Rotor rotational speed, rev/s
P : Power, W
R : Rotor radius, m
Rhub : Hub radius, m
r : Local radius, m
T : Thrust, N
TSR : Tip speed ratio
TSR : Local tip speed ratio
U : Inflow velocity, m/s
Utip : Blade tip velocity, m/s
Urated : Rated velocity, m/s
u´ : Velocity fluctuation, m/s
ua : Velocity average, m/s
α : Angle of attack, degrees
ε : Turbulence dissipation rate, m/s
μt : Turbulent viscosity
φ : Inflow angle, degrees
ρ : Fluid density, kg/m3
ω : Rotor rotational speed, rad/s
ωs : Specific dissipation rate, 1/s
θ : Twist angle, degrees
σ : Local solidity
ν : Kinematic viscosity, m2/s
1
CHAPTER 1: INTRODUCTION
1.1 Research background
With the rapid increase in population all over the world, existing non renewable energy
sources are depleting at an alarming rate. The unsustainable usage of fossil fuels, coal,
oil, natural gas is leading towards adverse climate change by constant emission of
greenhouse gases (Jaber, Badran, & Abu-Shikhah, 2004). Understanding the facts has led
the researchers to start finding ways to address this problem, such as inspiring the
development of new renewable energy technologies (Herring, 2006). Most of the
countries worldwide has paid much attention towards the production of “ green”
electricity from renewable energy sources to meet the ever-increasing energy demand
(Larcher & Tarascon, 2015) and lessen carbon emission.
In the ASEAN region, a small portion of energy produced comes from renewable
energy (4%) while energy from fossil fuels occupies 74%, combustible biomass and waste
occupies 22% (Low, 2012). In 2015, a collated data regarding the dependence of South
East Asian countries on oil and gas as the primary energy source was published by
(Quirapas et. al., 2015). The study showed that the countries like Brunai, Singapore,
Malaysia, Combodia are highly dependent on oil and gas as the primary energy source
(50% or more). Although considerable variation in natural energy resources is observed
among South East Asian countries, the significant amount of renewable energy available
in this region is not much exploited yet (Ölz & Beerepoot, 2010). Government policies
throughout this region are progressively supporting renewable energy and the green
environment. Several private organizations have their intension to invest in renewable
energy, which could mitigate climate change by means of the reduction in greenhouse gas
emissions. Being surrounded by water, ocean renewable energy is considered to be one
of the most relatively significant renewable energy source in the region. A recent study
2
has claimed about the prospect of harnessing ocean renewable energy (ORE) in the
region; however, there are numerous challenges to successfully exploit this potential
(Quirapas et al., 2015).
Ocean is the most power dense unexploited renewable energy source. Oceans are
considered to be capable of making a major contribution on future energy requirement
without risking serious damage to the environment. This is expected to have the potential
equal to or more than wind energy to fulfill our future electricity demands. Several forms
of energy including thermal, offshore wind, wave, tidal and ocean current energy exist in
ocean and the energy types are being inspected as major sources for power generation.
Because of the technical limitations and economic considerations, developments in
thermal energy is limited (Elghali et al., 2007). Tidal energy has the benefit of being less
responsive to climate change; while solar, wave, wind and HydroElectric Power (HEP)
are sensitive to the random changes in renewable fluxes brought due to the shifts of
climate regimes (Nicholls-Lee, 2011).
Most of the technology related to the popular tidal energy extraction device namely
horizontal axis tidal turbines (HATTs) is derived from the wind industry. However, the
working fluid in which they operate produces higher structural loading with additional
biological fouling, probable contact with the free surface, amplified material corrosion
and the probability of cavitation on rotor blade. Therefore, the design principle for a
HATT needs a high degree of robustness with minimum maintenance schedule to cut
down both installation and operational cost.
There are several design aspects that could be improved to maximize the energy
capture which is the most apparent aim of the device. The major turbine components that
have the key impact on energy extraction from the tidal flow are the rotor blades. The
existing devices are being suffered greatly from the low energy extraction capacity both
3
above and below rated condition. The efficiency, and hence, annual power extraction, of
a turbine could be amplified by altering and optimizing the blade design, while
maintaining minimum load on rotor. In this study, hydrodynamic performance
investigation for a novel horizontal axis tidal turbine with variable length blade has been
carried out.
1.2 Present status of renewable energy in Malaysia
Malaysian energy sector is basically dependent on oil (49.7%) and gas (20.1%) sources
as the primary energy source (STEC, 2013). In 2013, Malaysia's major energy supply
from natural gas was 39,973 ktoe (STEC, 2015).
In Malaysia, the target is to achieve 5% of renewable energy contribution for the
nation's electricity, which was about 1% in last decade (Yaakob, Ab Rashid, & Mukti,
2006). Intensive study on different ocean renewable energy sources are carried out in
Malaysia. Initially, an extensive study has been carried out by Yaakob et al. (2006) based
on the available oceanographic data of Malaysia to determine the prospect and suitability
of different ocean renewable energy sources (ocean thermal energy, tidal energy, wave
energy, salinity gradient and marine current) and concluded that the Malaysia is
comparatively less potent location for ocean-derived renewable energy. Mirzaei,
Tangang, and Juneng (2014) has studied the wave energy potential along the east coast
of Peninsular Malaysia and the findings showed that the annual average wave power for
selected sites are between 0.5 kW/m and 4.6 kW/m in the northern and southern section
of the coast.
However, Lim and Koh (2010) has identified potential tidal energy extraction sites
which were predicted to produce 14.5 GW h/yr. In Sabah, tidal energy potential was
predicted at 8188 GWh/yr from Kota Belud and 386 GWh/yr from Sibu. Although this is
a minor portion of the total energy demand but it still postures a probable solution to the
4
energy demand (Koh & Lim, 2010). Universiti Teknologi Malaysia (UTM) has started an
OTEC Centre which is founded in Kuala Lumpur but it would be observing Sabah as its
field of study and research. 1200 m depth is observed within 125 km distance from the
shore and the temperature at the bottom is about 41º C at 1200 m water depth (Yaakob,
2013).
The Straits of Malacca has identified to have a great potential for marine renewable
energy extraction because of its average tidal current speed of 2 ms-1 (4 knots) (Chong &
Lam, 2013). Marine Renewable Energy Research Group (MREUM), University of
Malaya has been conducting extensive research work on the tidal energy extraction
devices that are suitable to install this location since 2013. One of the major focus of the
studies is the hydrodynamic performance improvement of both horizontal and vertical
axis tidal turbine. As a part of the research work, a model horizontal axis tidal turbine
with variable length blade has been selected for present study.
1.3 Problem statement
Tidal stream energy extraction devices are mainly categorized into vertical axis and
horizontal axis turbines depending on the rotor’s axis of rotation. A typical vertical axis
tidal turbine contains multiple hydrofoil-shaped blades that are attached vertically
between a bottom and top support and the blades rotate perpendicular to the direction of
flow (Kiho, Shiono, & Suzuki, 1996). Horizontal axis tidal turbine (HATT) consists of
multiple blades which rotate parallel to the direction of flow. The majority of the tidal
turbines designed for energy extraction are the horizontal axis tidal turbines (Batten,
Bahaj, Molland, & Chaplin, 2008) with the advantages such as self-starting mechanism,
reduced gear coupling requirement, and pitch control system to avoid excess mechanical
load in high tidal stream velocities that has already been proven in similar fields like wind
5
engineering and propeller. World’s first 1.2 MW commercial scale tidal turbine SeaGen
is a twin rotor pitch controlled horizontal axis tidal turbine (Fraenkel, 2010).
The energy extraction by the tidal stream devices can be improved in some straight
forward ways. First one is the employment of improved blade design, which leads to
better hydrodynamic performance or higher efficiency, can be employed to maximize
output power of a tidal turbine. The maximum theoretical efficiency of an ideal kinetic
energy extraction device in a free stream is 59.3% (Yuce & Muratoglu, 2015; Fraenkel,
2014; Guney, 2011). In practice, after considering actual hydrodynamic performance and
efficiency losses associated in the generator and the gearbox, maximum power coefficient
achieved by most modern wind turbine is much lower than theoretical limit (52%)
(Pasupulati, Wallace, & Dawson, 2005). SeaGen has reported to achieve maximum 48%
rotor efficiency (Fraenkel, 2010). Therefore, there is a little scope of improvement while
considering associated cost involved in manufacturing that negates any benefits. Another
option of increasing energy output is to increase swept area of rotor using larger blades,
however, both the structure and the components must be built with appropriate ultimate
strength to survive in extreme weather condition involves extensive additional cost.
A few investigations in wind and ocean turbines have claimed that the use of ducts or
diffuser which increases the velocity of flow at the rotor plane, as a successful technology
to increase the power extraction efficiency. However, Fraenkel (2010) stated that the
device efficiency when referenced to the cross-section of entry is no better than for a
turbine of a similar swept-area to the cross-section of the entry flow to the duct. These
improvements in device performance are achieved through the application of different
controlling approaches (which maximize energy capture as well as cut down system
loads) such as adjustable speed, pitch, tethered, flexible blades and so on. All these control
systems existing in tidal turbine industry uses turbine blades with fixed length.
6
Variable length blade turbine is a comparatively new non-conventional power and load
control system which is until to date implemented particularly in horizontal axis turbines
in wind industry. This system is capable to improve energy extraction at the low wind
speed by extending the blade. Thus, the cost per unit electricity production will reduce
greatly and its extendibility/ fold ability of blade also offers an inexpensive way to
mitigate the site specific turbine design (Pasupulati et al., 2005). A similar concept was
proposed in 2010 for tidal turbine by the name of folding tidal turbine (FTT) was
mentioned by Lam and Bhatia (2013).
The cost per unit electricity production is relatively higher in marine industry than the
other sources of renewable energy since the fixed blade length turbines can extract energy
efficiently only at the rated tidal velocity for a specific site. Thus, implementation of this
simple mechanism can be a major solution to lessen this problem. However, limited
performance data is available for such type of wind turbine rotor and no performance
investigation data is found for tidal turbine. The present study aims to numerically
investigate hydrodynamic performance (thrust, moment and power coefficients) and
power capture at various tide speeds of a variable length blade HATT and compare the
obtained results with existing standard tidal turbine.
1.4 Aim and objectives of the study
The aim of the research is to propose an effective way to increase energy extraction
using variable length blades of horizontal axis tidal turbine (HATT). The following
objectives were set to meet the aim:
1. To validate blade element momentum theory (BEMT) based simulation
software QBlade and computational fluid dynamics (CFD) simulation
software ANSYS FLUENT used for the study.
7
2. To predict the non-dimensional performance characteristics of a variable
length blade horizontal axis tidal turbine (HATT) model at extended blade
conditions using the numerical simulation.
3. To evaluate the power extraction of the HATT model through BEMT and
CFD numerical modelling for different blade extensions.
1.5 Scope of the study
The focus of this research work is to investigate the hydrodynamic performance
of a model variable length blade HATT through numerical computation with the intention
of proposing an effective way to increase energy extraction by tidal turbine. Only the
rotor part (blades and hub) of the turbine is modelled and selected for performance study.
The other parts of the tidal turbine are considered to have negligible impact on the
performance.
BEMT is used to predict hydrodynamic performance parameters i.e. power, thrust and
torque coefficients and the associated power output of the full scale variable length blade
HATT for different blade extensions varying the tide speed. CFD is a time expensive
method of performance analysis, so, the performance is predicted for the rotor model with
maximum and minimum blade extension only to study the effect of blade extension. Mesh
density (coarse, medium and fine) and time step (0.1s~0.001s) dependence is inspected
for constant tip speed ratio (TSR) to find an optimum time step and mesh density for
faster and accurate solution. Power, thrust and torque coefficients and the power output
are evaluated for various tip speed ratio (TSR) altering the tide speed from 0.5 ms-1 to 2.5
ms-1.
8
1.6 Outline of the dissertation
The complete study is presented in the five different chapters given as:
Chapter one illustrates the general background, drives for the research on harnessing
energy from tidal stream. Objectives and scope of the research are also provided and then
concluded with the outline of the thesis through the study.
Chapter two outlines the devices under development and considerations of the blade
design. A review of previous research works related to tidal turbine hydrodynamics,
different power and load control system is provided. Theory behind two-dimensional
(2D) and three-dimensional (3D) computational methods (CFD and BEMT) are also
explained.
Chapter three consists of the description of the model HATT with variable length blade
that is used for the performance study. the step by step detail of simulation techniques
(CFD and BEMT) associated for the variable length blade HATT study.
Chapter four contains the result and discussion of the work. Validation results of the
BEMT code and CFD modelling used in the study is also provided in the section.
Essential graphs are given sequentially for discussion and resultant data has been
analyzed. The results obtained from computation have been evaluated towards a
comprehensive investigation of the capability in enhancing power capture.
Chapter five enumerates the summary of the whole work including the conclusions.
Finally, the thesis finishes with some suggestion on probable future works.
9
CHAPTER 2: LITERATURE REVIEW
Harnessing energy by Marine Current Energy Devices (MCEDs) offers a sustainable
and predictable alternative to other renewable energy technologies (Frost, 2016; Rourke,
Boyle, & Reynolds, 2010). Tidal stream technology has seen a rapid expansion in recent
years with over 50 devices now in development, several devices at the commercial
deployment stage and arrays of devices in the planning stage. This chapter outlines the
different types of device under development and identifies some of the design
considerations. An overview of the relevant theory used to assess the performance of a
HATT is discussed. Details of the underlying theory of the numerical modelling are also
given.
Tidal energy extraction devices
Tidal energy is one of the most used renewable energy for many decades, however the
requirements of power are significantly excess compared to the output of the preliminary
devices. A modern tidal power plant was built at La Rance, France in 1967 and was the
first successfully used commercial purpose device (Nicholls-Lee & Turnock, 2008).
Overshot waterwheel and paddlewheel are the primary hydro-mechanical devices which
have efficient bulb type hydroelectric turbine generator sets whereas, French barrage have
twenty-four, low head, 10MW, bulb type turbine generator sets and it has been working
for 40 years producing around 600 GWh/year (Perier, 2007).
In 1990, the first tidal turbine was introduced in Corran Narrows, Loch Linnhe,
Scotland, as a “proof of concept” model. The diameter of this turbine was 3.5 m and this
was designed for achieving a maximum 10 kW shaft power but recorded highest
consistent power was more than 15 kW (Macnaughton, Fraenkel, Paish, Hunter, &
Derrick, 1993). In September, 2003 world’s first tidal stream turbine grid connected was
10
installed in Norway coast near Kvalsund, which was an improved model of this turbine
with 3 MW designed capacity at 2.5 ms-1 current (Roach, 2003).
Most of the extraction devices of tidal energy can be categorized on the basis of fluid
motion type (linear or rotational) produced by them, the direction of the rotor axis or
linear motion and the insertion of flow acceleration mechanism. Devices can be horizontal
axis, vertical axis, hydrofoil, variable pitch, fixed pitch, zero head, lagoon, tethered,
barrage, ducted, water column, surface piercing, azimuthal, submerged, bi-directional.
All these devices can be divided into three basic categories which are vertical axis tidal
turbines (VATTs), horizontal axis tidal turbines (HATTs) and alternative devices.
Horizontal axis tidal turbines (HATTs)
a) Raised above condition (Fraenkel, 2010) b) Artistic impression of operation (Taylor,2007)
Figure 2.1: SeaGen device developed by Marine Current Turbine (MCT)
The operation of this type of tidal turbine is similar to horizontal axis or axial flow
wind turbines as the rotational axis is parallel to tidal flow and the device contains
hydrofoils radially structured around the hub. As the relative fluid flows over the airfoil
11
shaped rotating blades, it produces a pressure variance, and hereafter lift and drag forces.
The lift force completely dominates over the drag force which resulting turbine movement
around the rotational axis. This type of rotors are self-starting.
Horizontal axis tidal turbines (HATTs) tend to have higher efficiencies in comparison
with VATTs but are more complex in design. The typical blade design includes twist and
taper to achieve higher efficiency (Khan, Bhuyan, Iqbal, & Quaicoe, 2009). Generally,
peak efficiencies of HATTs range from around 39% to 48% (Jo, Lee, Kim, & Lee, 2013;
Mason-Jones, 2010).
Figure 2.2: Examples of horizontal axis tidal turbines
(SMD, 2016) (Tidal Energy, 2012)
(Power, 2015) Open Hydro, (2012) d) Deep Gen (Generation, 2010)
12
Existing commercial turbine SeaGen is a horizontal axis tidal turbine with 1.2MW
capacity, shown in Figure 2.1. It was developed by Marine Current Turbines (MCT) and
installed in UK waters in 2008. Horizontal axis tidal turbines (HATTs) are the mature and
most promising tidal turbine technologies. There are many forms of HATT, depending
on the basis of blades number and supporting structure type of the device to fix in position.
Other HATTs at various degrees of development (Figure 2.2) are the 1 MW TidEL
from SMD (SMD, 2016), OpenHydro (OpenHydro, 2012), Kinetic Hydropower System
(KHPS) by Verdant Power ( Verdant Power, 2015), the 500 kW Deep Gen from Tidal
Generation Ltd (Tidal Generation, 2010) (now Alstom) and the 1.2 MW Delta Stream
from Tidal Energy Ltd scheduled to be deployed at Ramsey Sound in Pembrokeshire in
the near future ( Tidal Energy, 2012).
Vertical axis tidal turbines
In vertical axis tidal turbines (VATTs), the rotation axis is perpendicular toward fluid
flow and these devices are either drag based or lift based. Lift based rotors operate in
similar manner of the horizontal axis turbines. On the other hand, drag based rotors
operate like water wheel. As the fluid hits the blade, it rotates the turbine. Savonius
turbines (Figure 2.3a) are drag based design and Darrieus turbines (Figure 2.3b) are lift
based design. A relatively new type of turbine is cycloidal vertical axis tidal turbine. The
operation concept of this turbine is much similar to a typical Darrieus vertical axis turbine.
Rotor blades of this turbine have an adjustable angle of attack and, each blade have the
ability to rotate upon their individual axis for process optimization.
The main advantage of a VATT is that it’s operational efficiency is independent of the
direction of tidal flow and can rotate the blades of rotor without any pitch or yaw
mechanism (Eriksson, Bernhoff, & Leijon, 2008). In addition, the simple straight-blade
design of VATTs requires less design and manufacturing costs while compared with
13
HATT blade (Khan et al., 2009). VATTs also produce less noise due to the lower
rotational speed.
One major disadvantage of VATTs is lower peak efficiency (Khan et al., 2009) which
is around 37% to 40% (Eriksson et al., 2008; Han, Park, Lee, Park, & Yi, 2013). Other
disadvantages of VATTs include the low starting torque and for this reason VATTs may
require starting mechanism (Khan et al., 2009); and the main reason for torque ripple is
to the change in attack angle with the rotation cycle (Eriksson et al., 2008).
a) Savonius turbine (Flowers, 2011) b) Darrieus turbine (Boyer, 2013)
Figure 2.3: Vertical axis tidal turbines
Alternative turbines
Working principle of some turbines is quite different from that of the horizontal and
vertical axis turbines. Oscillating hydrofoils and venturi effect devices (Figure 2.4a to
2.4b) are such two major types of the alternative devices. Oscillating hydrofoils capture
energy from tide using oscillatory motion apart from rotary motion. The arm of such
device is lifted as the hydroplane being lifted by currents. Hydraulic cylinders are actuated
14
at the arm or frame junction with this arm lift and the resulting high-pressure oil revolves
a hydraulic motor which, in turn, drives generator. Once the arm and hydroplane touches
their higher limit, the angle of hydroplane is upturned and the cycle is repeated (Goldin,
2001). The seabed mounted Stingray (Fraenkel, 2006), Pulse Stream (UK, 2011) and
bioSTREAM (Systems, 2013) are the examples of such type of device. At certain
instance, it only uses small percentage of the available energy and thus has an unlikely
high efficiency while compared with the vertical and horizontal axis turbines.
Venturi effect devices are two types. The first one is basically a HATT or VATT with
a duct around the device which improves the velocity of flow, for example the Lunar
Tidal Turbine (Energy, 2012) and the Neptune Proteus. The second type utilizes a venturi
and utilizes the drop in fluid pressure at the throat to draw a secondary fluid through a
distinct turbine, for example the Spectral Marine Energy Converter (VerdErg, 2013). This
design is advantageous as it can generate constant power and has no immersed moving
parts; however, pure venturi effect devices do not possess high relative energy extraction
efficiency that of other less complex turbines.
The advanced turbine designs include the HATTs which are used to power hydraulic
energy converters based onshore (Jones & Chao, 2009), Minesto connect the turbine into
a kite that is ‘‘flown’’ in the tidal stream (Minesto, 2015), Flumill uses two counter-
rotating helical screws mounted parallel to each other (Flumill, 2016), and Tidalsail
uses sails to convert current to electricity (Tidalsails, 2013).
15
a) bioStream (Systems, 2013) b) Lunar Tidal Turbine (Energy, 2012)
Figure 2.4: Examples of major alternative turbines
Securing, installation and maintenance
It is difficult and challenging to install and recover tools within a fast-flowing tidal
stream. The thrust on a marine turbine is considerably higher than that experienced by a
same rated power wind turbine, although the first one is much smaller. Therefore, holding
the rotor consistently and securely in place is the most important structural difficulties in
the severe and corrosive subsea environment (Kirke, 2005; Orme, Masters, & Mima,
2006).
To allow the operation of the HATT, there must be means of fixing the turbine at
some depth over the water column. The means by which the turbine is attached will
greatly depend on the depth of the water and proximity to the nearest onshore
service location (Snodin, 2001). Several concepts for the tidal turbines fixing are under
consideration that range from pile-mounted turbines to moored turbines, those subjected
to the sea bed and semi-submersible designs.
1. gravity base, in this case the device is tied to a weighted structure, as used
in OpenHydro (Figure 2.2e);
16
2. piled devices, like SeaGen these devices installed to either single or multiple
piles (Figure 2.1);
3. flexible moorings that are made up of of a tether with cables, chains or
ropes and
4. anchor which is used for securing the device to the seabed allowing
alignment with approaching tidal flows or waves. Some of these devices
involve contra-rotating rotors. Either the rotors have separate but parallel
axes of rotation, like TidEL (Figure 2.2a) or have the same axes of rotation,
as investigated by Clarke, Connor, Grant, Johnstone, & Ordonez-Sanchez
(2008). Consequently, zero net torque is produced and hence the device
remains aligned with the flow.
Other securing methods that have been proposed involve several hydrofoils
mounted to the structure which grip the device in position through down forces
resulted from tidal flows (EMEC, 2012). Whichever scheme is selected, all
reliability and safety related fes must be considered, and should be cost effective
(Harris, Johanning, & Wolfram, 2004). Pile based structures seems to be costly
and its application is limited up to depth 40 m by the recent technology ( Clarke,
Connor, Grant, Johnstone, & Ordonez-Sanchez, 2010).
Turbine blade design considerations
Turbine rotor blades being the key components of the energy conversion process, one
of the most major design aspect that have potential for improvement. As the horizontal
axis tidal turbine (HATT) design has to face different problems while functioning the
same structure in air; hence, the geometry and twist of blade vary from those used on the
HAWT. As the fluid density is different, the thrust experienced by horizontal axis tidal
turbine (HATT) is considerably more than that produced by a horizontal axis water
17
turbine (HAWT) of the same power at rated condition (Nicholls-Lee & Turnock, 2007),
although the swept area of HATT have been considerably small. Some other loads that
exist on a HATT but not experienced by HAWT involve cavitation, wave loading and
increased cyclic loads. The changes in static pressure and velocity over the vertical water
column also impose cyclic dynamic effects on the rotor blades.
Tidal turbine design is a balance between energy yield and unit energy production
cost. Several points are needed to consider while designing a tidal energy extraction
device including (Clarke, Connor, Grant, & Johnstone, 2007):
1. requirement of strong anchorages as extreme downstream drag forces are
produced because of strong tidal streams
2. corrosion or dependability of submerged components,
3. the turbine must be tied with anchor in such a way which permits periodic
maintenance and equipment repair, whereas this is expensive in the plain
sea condition and the expense should be reduced,
4. turbine efficiency reduction because of the marine growth on the rotor
blades,
5. impact on other wild life and marine traffic in the area where the device is
installed,
6. damage of the turbine and superstructure due to storm,
7. efficient energy harness from reverse current flows which might not be
completely rectilinear, and design for reliability and lifetime performance,
together with decommissioning as a HATT is expected to experience around
1x108 rotational cycles over a 20 years life.
8. device matching with generator, as the generator needs to run at nearly
constant rotor revolution speed or within an operational RPM range. In the
18
first case, a mechanism is required to adjust the pitch of the blade to control
output power, while in the second case a relatively simpler fixed pitch
blades can be used.
Turbine blade performance
Turbine performance assessment is dependent on three different characteristics
measures, these are:
Power coefficient, C� � ���������� (2.1)
where, P is the power produced from a rotor revolution speed of n revs/sec and M is
the generator torque. Considering the Reynolds number effects negligible, the actual
power harnessed by a geometrically similar turbine is proportional to the cube of the free
stream velocity and the rotor cross sectional area, as illustrated below:
P � �� C�ρAU! (2.2)
Thrust coefficient, C" � #$������ (2.3)
Here, T is thrust loading which should be repelled by the turbine supporting structures.
Torque coefficient, C� � ���������� (2.4)
C� � %&$'( (2.5)
Power coefficient, CP is boosted by controlling the pitch of the blades which may be
described by considering the tip speed ratio, TSR. This is the ratio of blade tip velocity,
Utip, to tide speed, U. With respect to performance, CP may be optimized for a particular
value of TSR. Similar to the wind industry, Utip should be varied through the pitch control
19
of the turbine blades to maintain a constant TSR as the tidal stream velocity is not
constant. Modelling studies suggest that for low velocity sites, a 23% increase in annual
energy capture is expected to achieve by the variable pitch devices in comparison with
the fixed pitch devices (Molland, Bahaj, Chaplin, & Batten, 2004).
The effective onset speed experienced by a local section will depend on the relative
involvement of the uninterrupted free-stream liquid velocity, U, and that, owing to the
speed of rotation,
) � 2+, � -�!. (2.6)
where, N is rotor blade revolutions per minute. For a turbine of radius, R, the tip speed
efficiently controls the relative velocity, and is defined as:
TSR � /(� (2.7)
Thus this ratio controls the overall performance of the turbine.
Power and mechanical load control systems
Power and blade load control can be implemented either by the mechanism that
entirely affecting the rotor, or via devices mounted on blades (or blade itself). Wind and
marine turbines use power and load control systems mainly to
i. improve power extraction at low wind/tide speeds and
ii. control the rated power of rotor at high wind/tide speeds to avoid overloading of
the generator.
20
Figure 2.5: Different control systems affecting blade performance
Figure 2.5 (adopted from Wiratama, 2012) shows a number of nonconventional and
conventional power and mechanisms of load control that affect the rotor performance.
Some control systems react only to the differences of fluid flow with extended time scales,
whereas others have shorter time scales and hence can be utilized for regulating the
impact of flow variations by the smaller time-scales. As shown in the figure, control
systems can be categorized depending on the controlling factors affecting the blade cross-
section (airfoil), blade span and twist.
All control systems mentioned in Figure 2.5, apart from the telescopic or variable
length blades, modify the performance of turbine by imposing a variation in the angle of
attack. The angle of attack is linked to the blade twist angle, blade pitch angle and inflow
angle.
The control methods also classified as active and passive. In the active control system,
regulating parameter have to be adjusted through commands from controller and is
independent of the turbine operational condition and this offers a whole control on power
21
and/or rotor blade loading. The flow kinematics nearby a blade part is guided by
regulating parameters (i.e., morphing airfoil, microtab, telescopic blades, flap), the total
blade (i.e., individual and conventional pitch control systems), or the whole rotor (i.e.
yaw, tilt and rotor speed).
In passive control system, the regulating parameter is influenced by the turbine
operational condition. Actually, no distinct regulator remains in place. The rotor blade
also acts as a regulator. Flow kinematics around the entire blade have been affected by
the variation of the turbine operational condition (e.g., tide speed) either by altering
inflow angle (i.e., stall-regulated blades), or by altering both blade elastic twist and inflow
angle (i.e., blades of adaptive). Turbine operational condition variation has been leads to
limited control on rotor power and/or blade loading.
In case of telescopic and adaptive blades as well as blades using morphing airfoils,
microtabs and flaps, modifications are essential to apply on the baseline rotor blade
topology and/or geometry and/or aerodynamic/hydrodynamic characteristics.
The following section describes the scope of using one of the simple but effective
nonconventional control mechanisms namely telescopic or variable length blade which is
mainly focused in the study. An overview of the performance analysis from previous
research works on wind turbine and tidal turbine will be discussed to analyze feasibility
of the performance study of telescopic/foldable or variable length blade HATT.
Variable length Blade control system
The concept of turbine with variable rotor diameter at various operation speeds is one
of the most recently revealed power and load control system in wind industry which was
patented to Dawson & Wallace (2009). This novel concept is shown in Figure 2.6. It is
shown that the wind turbine can increase the energy extraction by extending a tip blade
22
out of a root blade to change the diameter in low wind speeds and also reducing loads on
the rotor in high wind speed conditions by retracting the same (Dawson, 2006; GE Wind
Energy, 2006; Pasupulati et al., 2005).
A prototype was manufactured and field tested by a collaboration of DOE, Energy
Unlimited Inc. and Dawson (2006). A number of research and development areas
including aerodynamics, control, and manufacture optimization of the variable length
blades were identified after the field tests. Field tests have been showed that the energy
taken by the variable length bladed turbine (blade length varies from 7.5 m to 10.8 m)
was increased by 25% with the increase of blade length up to 44% (Pasupulati et al.,
2005).
An analytical investigation (McCoy & Griffin, 2006) showed agreement with field
data and stated that blade length increase by 28% could increase the energy capture by
21%. In addition, another analytical study by Sharma and Madawala (2012) showed that,
blade length increase by 50% can double the energy harnessed by the fixed bladed wind
turbine. Recently an analysis on a 10 kW telescopic blade horizontal axis wind turbine
(TBHAWT) indicated an increase in 18% energy output (Imraan, Sharma, & Flay, 2013).
Apart from improved energy yield and mechanical load control strategies, the variable
length blade rotor concept offers advantages including reduction in shipping and
installation cost and requirement of site specific rotor design. This concept is still at
development stage in wind industry and information about the aerodynamic performance
are limited.
In marine industry, a recent study investigated a similar concept of extendable bladed
vertical axis tidal turbine (VATT) namely, folding tidal turbine (FTT) and identified
significant reduction in transportation and installation cost (Lam & Bhatia, 2013).
However, hydrodynamic performance information of the tidal turbine to represent energy
23
capture phenomena is still unavailable. Such type of power control concept has not yet
been investigated for HATT to inspect viability of increasing the power extraction
particularly at low tide speed.
Figure 2.6: Variable length blade turbine concept
Two-dimensional foil performance
Two-dimensional foil performance is analyzed by performance per unit span i.e. in
terms of the drag, local lift and moment coefficients.
�� � 0�1�23�4 (2.8)
�� � 0�1�23�4 (2.9)
�� � 0�1�23�4� (2.10)
24
where, dL and dD are the lift and drag forces in the perpendicular and parallel
directions to W, and dm is the moment about z axis (Figure 2.7).
Figure 2.7: Foil orientation
Typical techniques of representing 2D performance data are in terms of change in
angle of attack or drag as a lift function. Lift data varies almost linearly with angle of
attack, until stall (where substantial areas of flow separation occur). Flow separation
changes the drag regime from one dominated by viscous shear (caused by the shearing of
a viscous fluid over the surface of a body due friction), to one where pressure drag (the
form drag created as a body is moved/moves through a viscous fluid) predominates
(Molland & Turnock, 2011).
At the stall condition, considerable drop in lift occurs because of the movement in the
effort centre of the developed force, and rapid increase in drag force occurs. In case of
stall, the speed of the process development is the vital factor. One of the turbine speed
control process employs stall regulation where the decrease in lift and increase in drag
controls the attainable driving torque. In this process, 3D effects are vital to the efficiency
with which stall regulation can be used.
25
Avoiding cavitation, maximum lift to drag ratio is the preferred operational condition
of foil. As the turbine rotates and the tip speed ratio modifies the effective angle of attack
experienced by the section is effected, thus the section behavior away from the optimum
is of significant importance. One efficient method for defining shape of section utilizes a
camber line to describe the mid-thickness position height, around which a deviation in
thickness is set as a function of thickness/chord ratio. A foil with zero camber is
symmetric in shape and will produce zero lift at zero angle of attack. A foil with camber
will produce positive lift at zero angle of attack with the lift value dependent on camber.
Blade element momentum theory
One of the most common and oldest computational method for wind and ocean turbine
performance analysis is BEMT, which combines the blade element theory and momentum
theory to inspect turbine performance. The momentum theory is based on the momentum
balance along the rotating annular stream tube passing through a turbine plane. It is
assumed that work done by the moving fluid passing through the turbine causes a pressure
loss at turbine plane. The induced velocity in axial and tangential direction due to the loss
of momentum can be determined by this theory.
In the blade element theory, each of the rotor blades are assumed to be divided into
infinite number of independent elements, as shown in Figure 2.8. The hydrodynamic
forces can be determined based on the condition of local inflow from the local airfoil’s
hydrodynamic characteristics. The lift and drag forces are calculated for each blade
section and then integrated along the blade span to get the moment and forces acting on
the turbine.
26
Figure 2.8: Blade element momentum analysis of HATT
In blade element momentum theory, these two approaches are coupled to provide an
iterative procedure that inspect induced axial and tangential velocity and then calculate
hydrodynamic forces. The detail of the BEMT based numerical code used for this study
is described by Hansen (2008).
Momentum theory
In momentum theory, turbine rotor is initially considered as an infinitely thin actuator
disk. The actuator disk represents a rotating device with infinite number of blades. As an
extractor of energy, the impact of the rotating mechanism depends on the step change in
static pressure and thus varies the total pressure along a streamline, whereas retaining
steadiness of flow speed. The outer stream tube of the upstream area (less than the disk
area) enlarges once passing the disk. The static pressure is initially below atmospheric
and the speed of flow less than free stream at this expansion region or wake. Since the
static pressure through the wake matches to the atmospheric pressure, additional
expansion happens and further reduction in the flow speed occurs.
27
Figure 2.9 demonstrates four stations along the stream tube: 1 – some way upstream
of the turbine rotor, 2 –just before the rotor blades, 3 – just after the rotor blades and 4 –
some way downstream of the turbine rotor. Between stations 2 and 3 energy is extracted
from the tide that results in a pressure change.
Assume P� = P5 and U2 = U3. Between stations 1 and 2; and between stations 3 and 4
also assume that the flow is frictionless. So Bernoulli’s equation can be applied which
yields,
6� + �� 89�� � 6� + �
� 89�� and 6! + �� 89!� � 65 + �
� 895 � (2.11)
Figure 2.9: Single stream tube analysis
Hence,
6� − 6! � �� 8(9�� − 95�) (2.12)
For flow down an annulus at position r and thickness dr, and as force equals to the
pressure divided by area:
28
@A � >6� − 6!?@B (2.13)
Then, @A � �� 8(9�� − 95�)@B (2.14)
Considering the drop in axial flow speed through the turbine, the axial induction factor,
a, is:
C � D1ED�D1
(2.15)
9� � 9�(1 − C) and 95 � 9�(1 − 2C) (2.16)
Substitution yields:
@A � �� 89��G4C(1 − C)I2+J@J (2.17)
Figure 2.10: Rotating annular stream tube
Now considering the rotating annular stream tube, Figure 2.10, with the same four
stations as described earlier; due to the turbine rotation, as the water passes between
stations 2 and 3 the blade wake also rotates. Consider angular momentum is conserved in
29
this annular stream tube. The blade wake is considered to rotate with an angular velocity,
C and the angular velocity of the rotating blades is ). Reminding from basic physics that:
Moment of Inertia of an annulus, K � LJ� (2.18)
Angular Moment, M � K� (2.19)
Torque, N � 0�0� � 0>OP?
0� � 0>�Q�P?0� � 0�
0� J�� (2.20)
So for a small element the corresponding torque will be:
@N � @LR�J� (2.21)
For the rotating annular element
@LR � 8B9� � 82+J@J9� (2.22)
Thus, @N � 82+J@J9��J� (2.23)
According to the definition of angular induction factor, a´
C´ � P�T (2.24)
Combination of equations (2.16), (2.23) and (2.24) provides the torque equation of the
rotating annular element of fluid as:
@N � 4C´(1 − C)+89�J!@J (2.25)
Therefore, momentum theory has yielded equations for the axial force (Equation 2.17)
and momentum (Equation 2.25) on an annular element of fluid.
30
Blade element theory
Two-dimensional (2D) foil characteristics can be used to calculate the lift and drag
forces acting on a turbine blade by means of blade element theory. Each blade is divided
into a number of 2D sections which are the blade elements. Blade element theory is
established based on two key assumptions:
i. There are no hydrodynamic interactions between the elements of blade.
ii. The forces acting on the elements of blade are only dependent on the drag and lift
coefficients.
The blade is divided into a number of small parts, and later the drag and lift forces
acting on each elements of blade are determined. The forces can be integrated along the
blade, and over one revolution of rotor (if the inflow is non-uniform) to find the forces
and moments generated by the whole turbine rotor. Figure 2.8 demonstrations forces and
velocities acting on a single blade element.
Each elements of blade experiences a little change in flow, as they have a variation in
rotational speed, twist angle and chord length. The relative velocity, W of the blade
section is a combination of the axial (1 – a)U1 and the tangential (1 + a´)ωr velocity at
the turbine rotor plane (see Figure 2.8). θ is the local blade pitch angle is the local angle
between the axis of chord and the rotational plane. The local angle of pitch is a
combination of the blade pitch angle, θp and the blade twist, β as θ = θp + β, where the
pitch angle is the angle between the tip chord axis and the rotor plane and the twist is the
angle measured relative to the tip chord. U is the angle between the rotational plane and
the relative velocity, W and Figure 2.8 illustrates the local angle of attack which is given
as:
V � U − W (2.26)
31
Further, it is seen that:
tan U � >�EY?D1>�ZY´?TQ (2.27)
By definition, the drag is parallel to the relative velocity, W and the lift is perpendicular
to the same velocity experienced by the airfoil due to the vortex system of a tidal turbine.
In addition, if the drag and lift coefficients CD and CL are known, the drag, D and lift, L
force per unit length can be obtained from the following equations:
M � �� 8[�\�� (2.28)
and:
] � �� 8[�\�� (2.29)
Where, c is the sectional blade chord length.
Thus, the normal and tangential forces acting on the rotor plane are given by:
� � M cos U + ] sin U (2.30)
And:
� M sin U − ] cos U (2.31)
The equations (2.30) and (2.31) are normalized with respect to �� 8[�\ yielding,
�� � �� cos U + �� sin U (2.32)
and:
� � �� sin U − �� cos U (2.32)
32
where,
�� � cd1�23�4 (2.33)
and:
� � ce1�23�4 (2.34)
From Figure 2.8, it is clear from the geometry that:
[ sin U � 9�>1 − C? (2.35)
and:
[ cos U � )J>1 − C´? (2.36)
In the control volume, the portion of the annular area enclosed by blades is defined as
solidity σ:
f>J? � 4>Q?g�-Q (2.37)
B defines the number of blades, r is the radial position of the control volume and c(r)
is the local chord.
Since Fi and F$ are the normal and tangential forces per length, the normal or thrust
force and the torque on the control volume of thickness dr are:
@A � j �@J (2.38)
and:
@N � Jj @J (2.39)
33
Combining equations 2.33, 2.35 and 2.38 yields:
@A � �� 8j D1�>�EY?�
klm�n \ ��@J (2.40)
Similarly, equations 2.34, 2.35, 2.36 and 2.39 provide the torque equation which can
be written as:
@N � �� 8j D1>�EY?TQ>�ZY´?
op� n qro n \ �@J (2.41)
Blade element momentum equations
Momentum theory provides two equations for axial thrust and torque which express
the values by flow parameters, and blade element theory provides two other equations for
the same parameters that express them by the foil’s lift and drag coefficients. These four
equations from momentum and blade element theory are solved to achieve final set of
equation.
Equating equations 2.17 and 2.40 and applying the definition of solidity, an expression
for the axial induction factor a is obtained:
C � �stuv�∅
xyd Z� (2.42)
Equating equations 2.25 and 2.41 an expression for the tangential induction factor a´
is obtained:
Cz � �stuv∅{|t∅
xye Z� (2.43)
Pure BEMT possess limitations, to overcome which correction factors are to be
introduced in the induction factor equations 2.42 to 2.43 obtained from basic momentum
and axial thrust equations. Main objective of the BEMT mainly determines a and Czusing
34
iterative method with the initial assumption of axial and tangential induction factor
values. The relative velocity W and inflow angle ϕ faced by each blade section can be
determined from the assumed induction factors. From inflow angle, the angle of attack is
determined and the associated lift and drag coefficients, �� and �� are obtained. Then
using the equations 2.44 and 2.45 new value of a and Czcan be calculated as follows:
Cm}~ � C + �s�tuv�∅
xydZ�
(2.44)
Czm}~ � Cz + �s�tuv∅{|t∅
xyeZ�
(2.45)
The original BEMT does not account three-dimensional effects like the tip vortices
and hub vortices into the wake on the induced velocity field. To compensate the
deficiency, the following corrections have been considered to obtain more robust
performance data.
i. Prandtl tip and hub loss factor is the most commonly used method for the
correction of two-dimensional profile data. However, a recent tip and hub loss
correction is proposed by Shen, Mikkelsen, Sørensen, and Bak (2005) which was
compared with Prandtl correction and found to provide more realistic performance
data along the blade and also shows better agreement with experimental data in a
study by Masters, Chapman, Willis, and Orme (2011). Therefore, for the turbine
simulation this method is used in the study.
�l� � -� cosE�[��E�.�>���?
�� ��� ∅�] (2.46)
where,
� � �E.���(g.���E��)
35
where, R is the radius of the rotor, r is the radius of the sectional element and
TSRr is the local speed ratio. Similarly, the hub loss factor is defined as in equation
2.47:
��� � -� cosE����E�.�G������I
����� ��� ∅�� (2.47)
Therefore, the total loss factor can be determined combining equations 2.46
and 2.47 as,
^ � �l�. ��� (2.48)
ii. Glauert proposed a correction for thrust coefficient, � is described in detail by
Hansen (2008). Buhl (2005) proposed an update of the correction that is used in
this study for the simulations of turbine. The correction in axial coefficient value
is given by,
C � �#cE�.E!�Pe>�.E!�c?Z��c>!cE5?!�cE�. (2.49)
Computational fluid dynamics (CFD)
A powerful tool that can be used to numerically analyze the HATTs performance is
through the use of discretization methods such as CFD, where the theory surrounding the
methodology is very well-established enabling, if required, the development of
customized code. However, ample commercial codes are available that have gone through
rigorous empirical testing and evaluation from both academic and industrial application.
This has the benefit to save time and the cost involved in the personalized software codes
development. The CFD software package ANSYS FLUENT and ANSYS Inc. another
software package GAMBIT 2.4.6 was used in a part of the work presented within this
document.
36
GAMBIT software package is designed to develop and mesh model for ANSYS
post processing. The output of the software is the input of ANSYS FLUENT simulation.
It has user friendly graphical user interface (GUI) that makes designing and meshing of
any model simple and intuitive. Its easy module helps user to design model from scratch,
can assign boundary and continuum type and has wide range of curve, face and volume
meshing options. The grid size can easily be handled by size function and quality can be
checked in terms of skewness.
ANSYS FLUENT applies the finite-volume approach to solve the governing
equations for a fluid flow field with predefined or user defined material properties for 2D
and 3D domains. It also permits the combined use of several physical models such as
those relating to cell motion, turbulence and interaction between free surface (FLUENT,
2006). Several turbulence models are available ranging between One-Equation Models
(OEM) and Large-Eddy Simulation (LES). With the increase in complexity of the viscous
models used for analysis computational cost also increases.
When utilizing the actual geometry of a HATT blade, the capacity of cell motion
application is vital to calculate the energy extracted from the moving fluid as the apparent
flow angle is dependent on the rotational velocity at a specific radius. However, the
computational time can be increased considerably due to the cell density toward the
structural surface boundaries when physical geometry is considered (FLUENT, 2006).
With the use of Reynolds Averaged Navier-Stokes (RANS) equations, turbulence models
can be applied to close the governing equations within significantly reduced solution
convergence time when compared with the extreme approaches like DNS.
FLUENTTM offers a range of viscous models that fall under the RANS category. These
include the one equation Spalart-Allmaras (SA) model and the two equation models such
as the Standard k-ε, Realizable k- ε, RNG k- ε, k-ω Shear Stress Transport (SST) and
37
Standard k-ω. VOF and Reynolds-Stress models are more computationally expensive
RANS equations. Other than these models, the Large-Eddy and Detached Eddy
Simulation are the most computationally expensive RANS equation based models. As
stated earlier, due to the large number of cells used in the CFD models the RANS equation
based models are computationally economic and therefore, the following discussion will
be limited to present the general form of these equations and to outline the meanings
together with a basic outline of the governing equations.
Several methods are available within ANSYS FLUENT software to simulate rotation.
2-D axisymmetric models, dynamic meshing and moving reference frame (MRF) are such
methods used for rotation simulation. Simple problems such as a rotating external
boundary can be simulated via 2-D axisymmetric models. In case of rotating body moving
through the fluid, dynamic mesh or MRF model is required. As will be discussed in
Chapter 3, a dynamic mesh /sliding mesh model was used for this work.
CFD provides thorough information on the forces acting on a turbine rotor and can be
used to optimize the design of initially developed turbine. For example, Mason-Jones
(2010) found optimum pitch angle 7o of a tidal turbine blade using BEM was later
observed to have an optimum angle 6º using CFD.
In earlier CFD works in the tidal stream turbine field, the tidal turbines were modelled
as a porous disk and the energy extraction by the disc was studied (Gant & Stallard, 2008).
Mason-Jones, Evans, O'Doherty, and O'Doherty (2008) developed a model horizontal
axis tidal turbine using the actual turbine geometry and this process was later being
followed by several research groups (Fleming, McIntosh, & Willden, 2013; McNaughton,
Rolfo, Apsley, Stallard, & Stansby, 2013; McSherry et al., 2011). Turbulence decay
through the length of the fluid domain has become apparent from these studies (Gant &
Stallard, 2008; Mason-Jones, 2010). Velocity profiles and bed shear have been included
38
in order to reduce this problem (Fleming et al., 2013), but this again dependent on exact
field data to provide accurate results.
The majority of CFD studies in this field have used either the k-ε model (Gant &
Stallard, 2008; Malki, Williams, Croft, Togneri, & Masters, 2013) or the k-ω Shear Stress
Transport (SST) model (Afgan et al., 2013; Fleming et al., 2013; McSherry et al., 2011)
although Mason-Jones et al. (2008) used the Reynolds Stress Model (RSM).
Further complex flow field can be simulated using Large Eddy Simulation (LES). LES
includes filtering the Navier-Stokes equations to eliminate eddies smaller than the grid
spacing, and retained the large eddies. The small scale turbulence is then modelled
assuming an isotropic eddy viscosity (ANSYS, 2010). LES needs a super refined mesh
and is thus computationally very costly.
A study on LES and RANS was performed by Afgan et al., (2013). They concluded
that the LES models were not significantly advantageous over the RANS models for
instantaneous and mean power and load predictions but was capable to capture unsteady
loads that were not captured by the RANS models. Therefore, it is expected that a LES
would offer valuable fatigue and life prediction data to the end of design process.
RANS viscous models
The instantaneous flow can be used to extract the mean (Ui) flow properties via the
use of ensemble averaging such that:
Up>x� , t) � lim i→¢
�i ∑ Up
>�?i¤�¥� >x� , t) (2.50)
Where: Ne = Ensemble average of experiments.
¦p(x� , t) � Up(x� , t) + u′p(x� , t) (2.51)
Mean Fluctuation
39
The Reynolds-averaged momentum equations are shown below where the Reynolds
stresses have to be evaluated through a model to close the set of equations:
8 �©��©� + Uª
©��©«�
� � − ©¬©«�
+ ©©«
�µ ©��©«
� + ©(�©« u
(2.52)
where:
Rp¯ � −8uz°u′±²²²²²²² also known as the Reynolds stresses. (2.53)
The Reynolds-Stress Model (RSM) and Eddy-Viscosity Models (EVM) can be used
to close RANS models. The RSM approach uses an eddy viscosity also known as the
turbulent viscosity (µ" ), equation 2.54, where the Boussinesq hypothesis is used by the
EVM approach. This hypothesis is reasonable for boundary layers, simple turbulent shear
flows and cases including channel flows, mixing layers and round jets. Equation 2.55 to
equation 2.60 are taken from the summary of the FLUENT introductory notes which
explains how µ" is calculated using different turbulence models.
Rp¯ � − 8uz°uz±²²²²²²² � µ" �©��©«
+ Uª©�©«�
� − 2
3µ"
©�³©«³
´ − 2
38µ´p¯ (2.54)
Based on dimensional analysis, µ" can be obtained from velocity and length scales so
that:
K=turbulent kinetic energy (m2/s2): K � 1
2 uz°uz±²²²²²²² (2.55)
ε = turbulence dissipation rate (m2/s2): ε � ν ©¹º»©«¼
�©¹º»©«¼
+ ©¹º¼©«»
�²²²²²²²²²²²²²²²²²²²² (2.56)
)o = specific dissipation rate (1/s): )o ∼ ¾¿ (2.57)
40
for:
Spalart-Allmaras: µ" � �ṽ (2.58)
Standard k-ε, RNG k- ε, Realizable k- ε: µ" = 8Cµ ¿�
¾ (2.59)
Standard k- ω, SST k-ω: µ" = 8Cµ 2¿
/ (2.60)
Each of these models solve transport equations for a modified turbulent viscosity in
the Spalart-Allmaras case and for two equation models k and ε for the Standard k- ε, RNG
k- ε and Realizable k- ε.
Summary
Among different tidal energy extraction devices, HATT is the most preferred method.
Blades are the main part of the HATT devices to contribute in power capture and are
required to operate efficiently in a wide range of tide speeds. BEMT and CFD are the
most powerful techniques to predict rotor performance associated with different turbine
blade design. The applications and the theory behind the simulation tools are presented.
A number of power and load control mechanism has been adapted modifying blade
design to improve performance. However, the recent devices having fixed length are site
specific and hence can’t extract much energy below the rated velocity. Alternatively,
HATT rotor with movable blade section enable the device to extract more energy below
the rated tide speeds and also can be used in different site. Model turbine with the variable
length blade mechanism can be more effective compared to the others. To author’s
knowledge, no performance and power extraction data is available for variable length
blade HATT which was investigated in the study.
41
CHAPTER 3: METHODOLOGY
A variable length blade turbine rotor model was simulated to evaluate the performance
using two-dimensional BEMT and three-dimensional CFD analysis. Generally, the two-
dimensional BEMT analysis is applied at the initial design stage. Further information on
the performance can be achieved from the three-dimensional CFD simulation technique.
A flow chart of the research procedure is shown in Figure 3.1.
Figure 3.1: Flow chart of the research methodology
42
Variable length blade HATT was modelled from modifying a reference turbine and
the procedure is illustrated in this chapter. In addition, the step by step description of the
numerical simulation techniques for performance analysis are described. Validation of
numerical modelling methods is essential before implementing to a research work. The
validation procedure of each simulation technique is also explained.
Variable length blade HATT modelling
A variable length blade HATT was modelled from the knowledge acquired from the
literature reviews. According to Wiratama (2012), the baseline rotor blade topology
and/or geometry is needed to be modified for the modelling of a telescopic or variable
length blade turbine and consequently the hydrodynamic characteristics are altered.
Hence, a three bladed 8 m diameter baseline HATT with fixed length blades was
considered in this study. Rated power of the turbine model was 100 kW at the rated tide
speed around 2 ms-1 with the rated rotational speed 24.72 rpm.
Figure 3.2: Baseline model tidal turbine blade profile
0
2
4
6
8
10
12
14
16
18
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1.2 1.7 2.2 2.7 3.2 3.7
Twis
t Ang
le (O
)
Cho
rd L
engt
h, (
m)
Rotor Radius (m)
Chord Length
Twist Angle
43
The turbine blade was composed of NACA 63-418 foil section. The NACA 63-series
blades are well known for stall delay and the roughness sensitivity is less than the other
NACA series foils specially NACA 4 and 5-series airfoils. Additionally, NACA 63-series
blade has relatively large minimum pressure coefficient that makes the airfoil resistant to
cavitation. The geometry details of the baseline turbine blade is presented in Figure 3.2
and the performance details are available in Ref. (Lee et al., 2011; Lee, Park, Kim, Rhee,
& Kim, 2012).
The model variable length blade HATT considered in the present study is shown in
Figure 3.3. Each blade of the model considered to be constructed of two blade sections
namely root and tip blade section. The root blade section is fixed to a hub having 7.2m
rotor diameter (excluding tip blade) and the tip section can be retracted and extended to
provide variable length feature.
Much attention was required to be paid when choosing the limit of the tip blade
extension length to avoid shallow tip immersion, excess thrust, torque and static load on
the blades. The tip blade was extendable from 0 m to maximum 1.6 m in length at different
operating conditions which allowed to vary the rotor diameter from 7.2 m to 10.4 m, being
-10% to 30% of the baseline turbine diameter.
The complete blade profile of the maximum extended condition is presented in Figure
3.4. The geometry of the root blade part kept same to the baseline rotor geometry. The
root blade section consisted of variable chord length and pitch angle along different blade
sections similar to a typical HATT (Figure 3.4). Reasonable chord ratio was maintained
between the two sections to allow smooth contraction and extension. Here, the tip blade
section included constant chord length of 0.235 m providing chord ratio 0.7 with tip chord
of the root blade section and have a constant pitch angle 2º.
44
Figure 3.3: Variable length blade HATT model
At the rated condition (2 ms-1 tide speed), the rotor was considered to be 10% extended
providing the rotor diameter same to the baseline HATT. Below the rated velocity, the
rotor blade could extend from 10% to 40% that increased rotor power capture while,
above the rated speed it could completely retract from 10% to 0% to cut down the
mechanical loads. The variable length blades provided smooth and complete control for
power and load. The model HATT is advantageous over the conventional turbines as it
appeared to control power capture and blade load efficiently.
45
Figure 3.4: Blade profile of model HATT
Two-dimensional (2D) BEMT simulation
This analysis provided information on the performance of the rotor for four different
tip blade extensions which were 10%, 20%, 30% and 40% of the baseline HATT rotor
radius. Therefore, the associated rotor radii considered were 4 m (3.6 m root blade radius
with 0.4 m tip blade length), 4.4 m, 4.8 m and 5.2 m. The results obtained are then
compared with the standard HATT of rotor diameter and geometry similar to baseline
turbine.
The 2D performance investigation of the variable length blade HATT was done by
QBlade software version 0.8. The software was developed based on BEM theory by the
Hermann Fӧttinger Institute at TU Berlin and proven efficient in wind turbine design.
This open source software was found user friendly as this single tool included all the
functionality required for wind turbine aerodynamics simulation and design without the
requirement to convert, import or process data from other sources (Marten, Wendler,
Pechlivanoglou, Nayeri, & Paschereit, 2013). The 2D panel code. XFoil was combined
024681012141618
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 5.2
Twis
t Ang
le (O
)
Cho
rd L
engt
h (m
)
Rotor Radius (m)
Chord LengthTwist Angle
46
within the GUI (Graphical User Interface) of QBlade to design foil and calculate lift and
drag over a range of angle of attacks for a certain airfoil and later the data has been used
in the performance prediction with blade element momentum theory.
Hydrofoil analysis
The 2D panel code XFoil (Drela, 1989) associated with QBlade was used to generate
the drag and lift coefficient data for the individual blade elements. The method proposed
by Snel et al. (1993) for extrapolation up to the stall delay angle was used to achieve lift
and drag coefficient. Further 360º polar extrapolations beyond the stall delay angle were
obtained by Viterna and Corrigan’s well established method for post stall predictions
(Viterna & Corrigan, 1982).
The 2D hydrofoil lift and drag coefficient data of the NACA 63-418 over a range of
angles of attack was calculated using Equation 2.28 and Equation 2.29 to obtain lift and
drag coefficient generated by the variable length blade tidal turbine. The simulations were
performed for a constant Reynolds number of 3.0 × 106. The variation in the Reynolds
number was supposed to be negligible along the blade profile, as a result the
hydrodynamic characteristics remain unchanged throughout the blade sections.
Rotor model generation
Four different rotor blade models with 10%, 20%, 30% and 40% tip blade extension
were generated using QBlade for four sets of performance investigation as mentioned
earlier. The blade geometry was defined by the parameters hub radius, rotor chord length,
pitch angle, type of airfoil section and associated 360º polar data. The blade sections in
the rotor design part were then directly used for the blade element momentum analysis.
47
Blade element momentum analysis
The rotor models and sectional hydrofoil characteristics were used in the BEM
simulation part. Theory involved with the QBlade BEMT code and the associated
equations were described in detail by Hansen (2008). Power, moment and thrust
coefficient curves were obtained from the BEM analysis part. Multiple parameter BEM
simulation part was used for power prediction at different tidal stream velocities.
QBlade BEMT code validation
A validation was mandatory for the QBlade BEMT code before employing it to predict
performance of the model HATT in present work. This new open source software has
proven its efficiency in wind industry already. But no such record was found stating the
method as a proven efficient technique for tidal turbine investigation.
To validate the BEMT code associated with QBlade software, two different HATT
were analysed and then compared with previous researchers’ experimental and numerical
investigation works (Bahaj, Batten, & McCann, 2007; Lee et al., 2012; Michelen, Murray,
Neary, & Barone, 2014)
Table 3.1: Particulars of the tidal turbines for QBlade BEMT code verification
Case 1 Case 2 Case 3
Rotor Radius (m) 0.4 10 4
Number of Blades 3 2 3
Airfoil Type NACA 63-8xx NACA 63-618 NACA 63-418 Set Angle, SA (º) 0, 5, 10 0 0 CPmax 0.45 (SA 0º)
0.46 (SA 5º)
0.38(SA 10º)
0.45 0.46
48
The airfoil types, principal dimensions, and operating conditions for the three different
HATT cases are presented in Table 3.1. The yaw, cone, and tilt angles were assumed to
be zero in these cases.
Three-dimensional CFD investigation method
The three-dimensional models of the maximum and minimum extended (40% and 10%
extended tip blade) variable length blade HATT were prepared and meshed in GAMBIT
2.4.6 and analysed using ANSYS FLUENT 15.0. The complete process involved four
major steps- geometry creation, mesh generation, solver setting and post processing.
The cases considered for current study are represented in Table 3.2. The torque, power
and thrust coefficient were evaluated varying tip speed ratios for optimum mesh and time
step. Then the performance data were compared with the obtained data from 2D BEMT
analysis and finally also with the typical baseline turbine.
Table 3.2: Cases considered in CFD simulation
Considerations Cases
Model 40%, 10% tip blade extended variable length blade tidal turbine
Mesh Dependence 1. Fine 2. Medium 3. Coarse
Time Step Dependence Transient time steps 0.005 s, 0.01 s, 0.05 s, 0.1 s and 0.2 s (Unsteady)
Tip Speed Ratio (TSR) 2 ~ 10 (For optimum mesh and time step determined from dependence study)
Tidal Velocities 0.5 ms-1 ~ 2.5 ms-1
Geometry preparation
Figure 3.5 represents the turbine geometry along with the coordinates created for
investigation. Using GAMBIT software as the pre-processor, faces (including connecting
pin to hub) of the blade profiles were created. All faces were stitched to form the volume
49
of the blade. The faces on the hub were also attached to produce another volume. The
turbine blade volume was then aligned with the Y-axis and the rotational centre of the
hub with the X-axis. By moving the blade pin along the Y-axis the outer radius of the
rotor was adjusted with the blade positioned so that the upstream flow face was along the
positive X-axis as seen from Figure 3.5. Then three individual blade volumes and hub
were combined to form a single turbine volume containing three blade volumes around
the X-axis and the hub volume.
Figure 3.5: 3D turbine rotor geometry
To simulate turbine rotation, the HATT volume was subtracted and removed from a
cylindrical volume by the Boolean function so that the cylindrical volume persisted with
a hollow section inside identical to the turbine rotor assembly (Figure 3.6). The length of
cylindrical subdomain was selected equal to 0.6D (D is turbine diameter) following
research work by Mason Jones (2010) which mentioned that the variation in the length of
this domain has no significant impact on the torque, power and axial load data for a tidal
turbine. For the model created for the present study a relative distance, was maintained
50
between the edge of the rotor and the tip of the blade domain to avoid poor result and
numerical dispersion close to the non-conformal interface.
Figure 3.6: Turbine geometry surrounded by sub-domain and main domain
The computational/ main domain’s, surrounding the cylindrical sub-domain, extent
was a length of 9D and a radius of 3D, where D represented the turbine diameter as shown
in Figure 3.6. The inlet and outlet boundaries were located at 3D upstream and 6D
downstream. These dimensions were selected following the study by Lee et al. (2012) to
predict performance of the turbine. The Boolean function is again used to subtract the
cylindrical sub-domain of the main domain.
Main domain
Extended blade rotor geometry
Cylindrical subdomain
51
Mesh generation
The rotor domain and the main domain both were meshed with tetra-hybrid
unstructured mesh (see Figure 3.7). Several meshing schemes were adopted to mesh the
rotor domain with different mesh growth rate while keeping the mesh density of the main
domain constant to find an optimum mesh density for performance study. Rotor mesh
started from turbine blades and hub and ended to the edges of cylindrical subdomain.
a) Rotor mesh b) Mesh on blade surface
c) Complete domain mesh
Figure 3.7: Meshing of blade surface, rotor and main domain
52
The mesh element growth rate factor was varied, ranging from 1.08 to default 1.2.
Mesh element size and the growth rate was selected in such a way so that skews could be
avoided. Main domain or stator mesh started from rotor domain and ended to the edges
of the cylindrical main domain with mesh element growth rate factor 1.15.
The mesh quality is determined by the mesh metric skewness. Meshed cells are
classified as bad with the skewness above 0.9, poor if they have a skewness of 0.75-0.9,
fair when the skewness ranges 0.5- 0.75, good when the skewness ranges 0.25-0.5 and
excellent when the skewness ranges 0-0.25. In case of 3D modelling, it is suggested that
“most cells should be good or better, but a small percentage will generally be in the fair
range and there are usually even a few poor cells” (ANSYS, 2010).
CFD solver setting
ANSYS FLUENT solvers are mainly two types, density-based and pressure-based.
Pressure-based solvers were at first used for slow speed, incompressible flows and hence
a pressure-based solver was used for the work discussed in this study. The Least Squares
Cell Based method was used to evaluate the gradients of the variables. The semi-implicit
method for pressure-linked equations (SIMPLE) was selected, which uses the relationship
between velocity and pressure corrections to enforce mass conservation, to obtain the
pressure field.
The values of the flow variables at the cell faces are interpolated from the cell centre
values. The values of pressure and momentum were interpolated using the second order
and second order upwind scheme respectively. The turbulent kinetic energy, specific
dissipation rate was found using the first order upwind scheme. The under-relaxation
factors, found within the solution controls menu were left at the default values. Other
major solver settings are specified in Table 3.3.
53
Table 3.3: Important solver settings for CFD simulation
Parameter Description
Turbulence model k-ω SST
Inlet Velocity inlet Outlet Pressure outlet
Material type Water-liquid
Density 1025 kg/m3
Rotor rotation type Sliding mesh/ Mesh motion Time stepping method Transient
The inlet of the main domain was set as a velocity inlet using the velocity specification
process. The velocity magnitude for the CFD model has been changed to cover the turbine
operational range. The outlet of the main domain was set as a pressure outlet with 0 Pa
gauge pressure. The backflow direction specification system was set as normal to
boundary. The turbulence specification process and related values were the same as for
the inlet. The outer boundaries of the models were set as stationary walls with default
roughness values, but the shear condition was set to specified shear with shear stress
components of 0 Pa in all directions for all boundaries.
Turbine rotation was simulated by selecting mesh motion in the cell zone conditions
for the cylindrical sub-domain. The rotation-axis was set at origin (0, 0, 0) of the
coordinate system and the rotation-axis direction was along the X-axis. The velocity of
rotation was set and the inlet velocity was varied according to the change in tide speeds.
The lateral position of turbine is generally fixed at site; hence the lateral velocity was set
0 ms-1 in all three directions. Although the calculation requires more time while compared
to moving reference frame (MRF), sliding mesh/ mesh motion was selected because it
could consider the impact of relative components and even the first order upwind provides
54
acceptable results. All the models continued to iterate until the residuals had stabilized rather
than setting a convergence target.
Post processing (calculation of performance coefficients and power)
The torque was determined from the model by setting up a force report and selecting
the moment option. The moment centre was set at the origin of the axes X, Y and Z and
the X-axis was set as the moment axis. Each blade and the hub were selected as the wall
zones and the results were printed to the text user interface where the torque resulting
from each blade and the hub was displayed separately as well as the net torque for the
whole turbine.
The power was then calculated multiplying the total torque by the rotational speed. It
should be noted that the theoretical maximum extractable power is 59.3% of the available
upstream power. The axial load or thrust was determined by setting up a force report and
selecting the force option. The direction vector was set along the X-axis and again the
blades and the hub were selected as the wall zones. Once more the results were printed to
the text user interface and the axial load on each blade and the hub was given as well as
the net axial load. Finally torque, power and thrust coefficients were determined from the
equation 2.1, equation 2.3 and equation 2.4 mentioned earlier in section 2.4.
Mesh selection
Fine mesh densities are too computationally costly as an extensive number of runs
involved while mesh with coarse density provide inaccurate results. A Grid Independence
Test (GIT) is performed using six different meshing schemes from three mesh types as
shown in Table 3.4. In each meshing scheme, the rotor mesh volume was varied to obtain
the optimum mesh scheme for further computation as described previously. It was
observed from the grid dependence study that utilizing the k-ω SST turbulence model and
maximum mesh density (2.91 million), roughly 17 hrs were required to converge.
55
Additionally, this mesh scheme of the model required to use the model memory within
2% of the workstation maximum RAM, any further increase in mesh density surpassed
the available memory. On the other hand, model with 1.65 million mesh density took
roughly 9 hrs for convergence. Using this medium mesh scheme, peak CP value was found
0.386 (Table 3.5). Hence, the reduction in 8 hrs convergence time, the variation in
calculating value was very small (~2%). Because of the asymptotic variation in
performance and the huge number of runs required to create point by point performance
curves, the mesh scheme with 1.65 million rotor mesh volume was applied for every
single model which have minor impact on the output data.
Table 3.4: Mesh dependent peak CP checks for maximum extended model
Mesh Type
No of Mesh in Rotor Volume
No of Mesh in Stator Volume
Time
Step
Tip Speed Ratio
Power Coefficient
Percentage Deviation
(million) (million) (s) (TSR) CP (%)
Coarse 0.89
0.42 0.01 8
0.338 14.43 1.14 0.362 8.35
Medium 1.35 0.37 6.33 1.65 0.386 2.28
Fine 2.54 0.394 0.25 2.91 0.395 -
Time step selection
The optimum meshing scheme obtained (1.65 million rotor mesh density) was selected
for the time dependence study. Five different transient time steps ranging from 0.2 s to
0.005 s were considered (see Table 3.5). Using small time steps are computationally more
precise, but very expensive in terms of time consumption.
Here, using 0.005 s time step with optimum mesh density 1.65 million, roughly 23 hrs
were required to converge. On the other hand, for 0.01 s time step model with 1.65 million
56
mesh density took roughly 9 hrs for convergence. Using this time step, peak CP value was
found 0.386. Hence, reducing 14 hrs convergence time, the variation in calculating value
found less than 1%. Further increase in time step might affect the peak CP value
calculation as more than 6% variation was observed in that case. Therefore, 0.01 s time
step was selected as the optimum time step for the performance computation in the study.
Table 3.5: Time dependent peak CP checks for maximum extended model
Time Step
No of Mesh in Rotor
Volume
No of Mesh in Stator
Volume
Tip Speed Ratio
Power Coefficient
Percentage Deviation
(s) (million) (million) (TSR) CP (%)
0.2
1.65 0.42 8
0.312 19.79 0.1 0.348 10.54 0.05 0.364 6.43 0.01 0.386 0.77 0.005 0.389 -
CFD FLUENT model validation
In order to validate the CFD modelling technique a three bladed typical tidal turbine
performance has been assessed and the comparison was made with results from a previous
study (Song, Kim, Do, Rhee, Lee, & Hyun, 2012). The geometry and technical details of
the turbine model is available in the mentioned Ref.
The method of investigation is similar to that followed for the model variable length
blade HATT as described in the previous sections. The geometry was developed and
meshed using GAMBIT. The solver setting and post processing was done in ANSYS
FLUENT with k-ω SST model. Here, the power coefficient is then calculated for different
tip speed ratio changing tide speeds and compared with the CFD and experimental results
from previous study.
57
CHAPTER 4: RESULTS AND DISCUSSION
The focus of the thesis was to understand the design and hydrodynamic characteristics
of variable length blade HATT. All performance studies for different blade extensions
were performed at zero degree (0º) set angle. In both BEMT and CFD investigation part,
the rotor performance was studied at and below the rated conditions and compared with
the conventional HATT.
The detailed results from the validation studies of the simulation tools are provided in
section 4.1 before presenting the performance results for the present model. The results
obtained to achieve the objectives are discussed comprehensively in the following
sections (Section 4.2 to 4.3). Section 4.2 and 4.3 included the performance results from
BEMT code and the comparative analysis of achieved data from the CFD study. The
comparison of performance and power extraction data between the model turbine and the
typical baseline HATT was also inserted in the sections.
4.1 Validation of the simulation techniques
4.1.1 Validation results of QBlade simulation tool
The validation of the QBlade BEMT code used for the two-dimensional simulation of
the present model HATT was performed using three different cases that included a range
of well-established simulation tools and experimental results.
In the first case, the QBlade BEMT code was validated (See Figure 4.1 to Figure 4.6)
against two well established simulation techniques (commercial software code GH-Tidal
Bladed and academic code SERG-Tidal) and the cavitation tunnel experiment data by
Bahaj et al. (2007). In the second case, the two-bladed HATT reference model, DOE RM1
was used. Here, the QBlade BEMT code was compared with the results from open source
software CACTUS and the United States Naval Academy’s (USNA) experimental results
58
mentioned in Michelen et al. (2014) as shown in Figure 4.7. Similarly, in the last case,
again a comparison of the QBlade BEMT code with results from the previous BEMT
code, CFD analysis and towing tank experiment by Lee et al. (2012) was performed
(Figure 4.8).
Figure 4.1 Power coefficient data comparison for QBlade BEMT code validation
(Case 1, set angle 0º)
Figure 4.2 Power coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 5º)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
2 3 4 5 6 7 8 9 10
Cp
Tip Speed Ratio (TSR)
SERG-TidalGH-TidalQblade BEMTCavitation Tunnel Exp.
. Bahaj et al. (2007). Bahaj et al. (2007)
Bahaj et al. (2007)
0.000.050.100.150.200.250.300.350.400.450.50
2 3 4 5 6 7 8 9 10
Cp
Tip Speed Ratio (TSR)
SERG-TidalGH-TidalQblade BEMTCavitation Tunnel Exp.
. Bahaj et al. (2007). Bahaj et al. (2007)
. Bahaj et al. (2007)
59
Figure 4.3: Power coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 10º)
Figure 4.4: Thrust coefficient data comparison for QBlade BEMT code validation (Case 1, set angle 0º)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
2 3 4 5 6 7 8 9 10
Cp
Tip Speed Ratio (TSR)
SERG-Tidal
GH-Tidal
Qblade BEMT
Cavitation Tunnel Exp.
. Bahaj et al. (2007)
. Bahaj et al. (2007)
. Bahaj et al. (2007)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
2 3 4 5 6 7 8 9 10
Ct
Tip Speed Ratio (TSR)
SERG-Tidal
GH-TidalQblade BEMT
Cavitation Tunnel Exp.
. Bahaj et al. (2007)
. Bahaj et al. (2007)
. Bahaj et al. (2007)
60
Figure 4.5: Thrust coefficient data comparison for QBlade BEMT code
validation (Case 1, set angle 5º)
Figure 4.6: Axial thrust coefficient data comparison for QBlade BEMT code
validation (Case 1, set angle 10º)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
2 4 6 8 10
Ct
Tip Speed Ratio (TSR)
SERG-Tidal
GH-Tidal
Qblade BEMT
Cavitation Tunnel Exp.
. Bahaj et al. (2007)
. Bahaj et al. (2007)
. Bahaj et al. (2007)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
2 3 4 5 6 7 8 9 10
Ct
Tip Speed Ratio (TSR)
SERG-TidalGH-TidalQblade BEMTCavitation Tunnel Exp.. Bahaj et al. (2007)
. Bahaj et al. (2007). Bahaj et al. (2007)
61
Figure 4.7: Power coefficient data comparison for QBlade BEMT code
validation (Case 2)
Figure 4.8: Power coefficient data comparison for QBlade BEMT code
validation (Case 3)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
5 7 9 11 13
Cp
Tip Speed Ratio (TSR)
CACTUS1Foil
CACTUS1Foil+Cyl
Qblade BEMT
USNA1 Exp.. Michelen et al. (2014)
USNA2 Exp.. Michelen et al.(2014)
. Michelen et al. (2014)
. Michelen et al. (2014)
0.00
0.10
0.20
0.30
0.40
0.50
0 2 4 6 8 10 12
Cp
Tip Speed Ratio (TSR)
Reference BEMT
CFD
Qblade BEMT
Towing Tank Exp.
QBlade BEMT
. Lee et al. (2012)
Lee et al. (2012)
. Lee et al. (2012)
62
A comparative analysis of the power coefficient data for all the mentioned cases is
shown in Table 4.1. The results from QBlade BEMT was more close to the experimental
results for all three cases (Figure 4.1 to Figure 4.8). Thus, it was evident that the QBlade
BEMT is able to predict the performance more accurately than the other numerical
simulation techniques used in the previous studies. Therefore, it was used to predict the
performance of the model variable length blade HATT at the initial design stage.
Table 4.1: Comparison of hydrodynamic performance data among different
investigations
Case Tip Speed Ratio (TSR)
Investigation Techniques
CP Ct
1 4.8
SERG-Tidal
0.45 (SA 0º)
0.45 (SA 5º
0.36 (SA 10º))
0.81 (SA 0º)
0.67 (SA 5º)
0.49 (SA 10º)
GH-Tidal
0.44 (SA 0º)
0.435 (SA 5º)
0.39 (SA 10º)
0.80 (SA 0º)
0.69 (SA 5º)
0.52 (SA 10º)
Cavitation Tunnel Experiment
0.45 (SA 0º)
0.45 (SA 5º)
0.375(SA 10º)
0.87 (SA 0º)
0.71 (SA 5º)
0.53 (SA 10º)
QBlade BEMT
0.43 (SA 0º)
0.46 (SA 5º)
0.40 (SA 10º)
0.78 (SA 0º)
0.65 (SA 5º)
0.50(SA 10º) 2 6.5 CACTUS1Foil 0.50 --- CACTUS1Foil+Cyl 0.40 --- USNA1 Experiment 0.45 --- USNA2 Experiment 0.44 --- QBlade BEMT 0.43 --- 3 5.5 Reference BEMT 0.46 --- CFD 0.47 ---
Towing Tank Exp. (ω=250 rpm)
0.44 ---
QBlade BEMT 0.43 ---
63
4.1.2 Validation results of CFD simulation tool
CFD results are more reliable compared to the two-dimensional simulation due to its
ability to capture the flow dynamics in detail manner. As the process was time consuming,
it was tough to validate CFD three-dimensional simulation technique using wide range of
data involving different cases like BEMT code validation in previous section 4.1.1. Here,
the CFD data were validated against another CFD simulation and towing tank experiment
data by Lee et al. (2012). The data from the present CFD was observed more close to the
experimental data. Therefore, the method can generate more reliable data compared to
other CFD simulation used for previous performance studies. After getting confirmation
from the validation study, it was selected to be used for power output and non-
dimensional performance coefficients prediction of the model variable length blade
HATT in the present study.
Figure 4.9: Power coefficient data comparison for CFD technique validation
0.00
0.10
0.20
0.30
0.40
0.50
2 4 6 8 10 12
Cp
Tip Speed Ratio, TSR
Towing Tank Exp. (270rpm) by Song et al. (2012)Towing Tank Exp. (330rpm) by Song et al. (2012)Towing Tank Exp. (410 rpm) by Song et al. (2012)CFD by Song et al. (2012)Present CFD
64
4.2 Non dimensional performance characteristics of HATT model
Torque, power and thrust coefficients are the key indicators of a turbine performance.
These three performance parameters of the variable length blade HATT model were
calculated by both BEMT and CFD methods after validation.
4.2.1 Performance coefficients prediction from BEMT study
The performance analysis was done and compared for four blade extensions (10%,
20%, 30% and 40%) for the variable length blade HATT and compared with the
performance data of the baseline HATT. Initially, two-dimensional foil performance of
NACA-63418 hydrofoil was predicted. The lift and drag coefficient data of NACA-63418
hydrofoil obtained were shown in Figure 4.10 and Figure 4.11.
Figure 4.10: Lift coefficient vs angle of attack for NACA-63418 hydrofoil
-1.5
-1
-0.5
0
0.5
1
1.5
2
-10 -5 0 5 10 15 20
Lift
Coe
ffici
ent,
C l
Angle of Attack (degree)
Xfoil
Abbott and von Doenhoff (1959)
CFD Lee et al.(2012)
65
Figure 4.11: Drag coefficient vs angle of attack for NACA-63418 hydrofoil
The obtained data were compared with the experimental data (Abbott & von Doenhoff,
1959) and the CFD data (Lee et al., 2012). These data were found to fit well with the
experimental results for the lift coefficient. On the other hand, the XFoil slightly
underestimated the drag data that matches with the statement by Molland et al. (2004).
The non-dimensional performance curves obtained from the simulation are
represented by Figure 4.12 to Figure 4.14. Figure 4.12 shows the effect of blade extension
on the power coefficient of the model HATT. In all cases, the CP curves were found to be
varied in a same manner with tip speed ratio (TSR).
Improvement in the peak power coefficient was observed with the increase in tip blade
extension, although the tip blade profile was not optimized for maximum power
production. For 40% extension i.e., 10.4 m diameter of the model HATT, predicted
maximum CP was 0.476 at tip speed ratio (TSR) around 8.1 and the value was 10% more
than that of the 10% extended (0.433) bladed device at rated condition. Almost similar
0
0.01
0.02
0.03
0.04
0.05
-10 -5 0 5 10
Dra
g C
oeffi
cien
t, C d
Angle of Attack (degree)
XFoilExperiment Abbott and von Doenhoff (1959)CFD Lee et al. (2012)
66
maximum CP value was obtained from a study by Goundar & Ahmed (2013) for the
optimum design of a three bladed standard HATT of 10 m diameter.
In addition, following the similar trend, increase in swept area of the model HATT
rotating with fixed rotational speed resulted in better CP value at lower tidal velocity.
Here, for 10% blade extension, the maximum CP was achieved at velocity 2.07 ms-1 while
with 40% extension, it was achieved at lower velocity 1.7 ms-1. Similarly, for the 20%
and 30% extended tip blade, the maximum CP was calculated 0.454 and 0.467 at velocity
1.9 ms-1 and 1.8 ms-1 for TSR 6 and 7.5 respectively.
Figure 4.12: Power coefficient (CP) vs. TSR with different tip blade extensions
The power coefficient improvement with the increase in blade extensions were
identified for higher tip speed ratios (TSRs) only (Figure 4.12). At lower TSRs, the power
coefficient values reduced considerably with the increase in blade. Since, power
coefficient is the ratio of the extracted power by the rotor and the available power over
67
the rotor area. Drop in the power coefficient at lower TSRs, despite being able to extract
more power (Figure 4.17), was due to the increase in blade length that consequently
caused an increase in the rotor area.
.
Figure 4.13: Torque coefficient (CM) vs. TSR with different tip blade extensions
Figure 4.13 and Figure 4.14 represents non-dimensional torque and thrust curves
associated with different conditions. Both moment and axial thrust coefficients (Figure
4.13 and Figure 4.14) were also observed to be improved with the increase in the blade
length at higher TSRs, but declined at lower TSRs following power coefficients as
mentioned for power coefficient. The maximum moment coefficient values were reduced
with the increase in blade length while the operational TSR ranges appeared to increase.
0.00
0.02
0.04
0.06
0.08
0.10
0.12
2 4 6 8 10 12 14 16 18
CM
Tip Speed Ratio (TSR)
Standard HATT30% Extension20% Extension10% Extension40% Extension
68
Figure 4.14: Axial thrust coefficient (Ct) vs. TSR with different tip blade extensions
It was also observed from the power, moment and thrust coefficient curves that, the
model with 10% extended tip blade and the standard HATT of the same rotor radius
exhibited an almost identical performance. Thus, the presence of small step change could
not affect to the performance of the present model. Moreover, the variable length blade
feature ensured the performance increment at lower tide speeds.
4.2.2 Performance coefficients prediction from CFD study
To understand the effect of variable length blade on the performance for maximum
and minimum blade extensions (40% and 10%), more accurate CFD analysis of the model
turbine were performed. Initially predicted performance data was also verified from
comparative analysis.
The change in power, thrust and moment coefficients with the increase in blade length
were observed similar to the BEMT results. Thus, the non-dimensional performance
coefficients at low TSR range was found to reduce with increment in blade extension and
0.0
0.2
0.4
0.6
0.8
1.0
2 4 6 8 10 12 14 16
Ct
Tip Speed Ratio (TSR)
Standard HATT30% Extension20% Extension10% Extension40% Extension
69
vice versa. Moreover, performance characteristics data achieved from the CFD
investigation fitted well with the results predicted from BEMT at rated velocity condition
(i.e. with 10% extended blade) as shown in Figure 4.15. Hence, the CFD results again
confirmed that the model considered in the research exhibited similar non-dimensional
performance characteristics with the baseline turbine at the rated condition. This indicated
that the inclusion of slight step change in chord length has negligible impact on the rotor
performance for similar rotor diameter and foil characteristics.
Figure 4.15: Performance coefficient curves of 10% extended blades from CFD analysis
On the other hand, for the fully extended tip blade condition, the feature revealed was
different from the results obtained from the BEMT investigation (Figure 4.16). A drop in
peak CP value was observed as the blade length varies from minimum to maximum. Here,
the 10% and 40% extended blades have highest CP value of 0.423 and 0.386 at TSRs
approximately 5 and 8 respectively. Thus, the turbine performance appeared to be reduced
0
0.05
0.1
0.15
0.2
0.25
0.3
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
4 5 6 7 8 9 10 11 12
Cp Curve Cm Curve Ct Curve
Cp,
Ct
Tip Speed Ratio (TSR)
CM
CM Curve
70
by 9% despite of increasing the rotor swept area. In addition, axial thrust load on the
model was increased with the blade extension. An explanation of such opposite
phenomenon was given by Afjeh & Keith (1989) for a horizontal axis tidal turbine with
tip control. The reason behind such performance drop was due to the presence of
additional drag force at the step change in chord length region. This supplementary step
loss to some level abolishes the lift contribution that achieved from the added length of
tip blade. This also elucidated the limitation of the BEMT code in case of predicting
performance accurately at extended blade condition. The code is needed to modify by
including the step loss factor with tip and hub loss factor.
Figure 4.16: Performance coefficient curves of 40% extended blades from CFD analysis
4.3 Power extraction
Apart from the conventional methods of improving performance of tidal turbines, an
advanced system of increasing power extraction using variable length blade was
0
0.04
0.08
0.12
0.16
0.2
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
5 6 7 8 9 10 11 12 13 14
Ct Curve Cp Curve Cm Curve
Cp,
Ct
Tip Speed Ratio (TSR)
CM
CM Curve
71
examined. In both analyses, the power output of the variable length blade HATT model
was calculated for the conditions described in the previous section (see section 4.2).
4.3.1 Power prediction from BEMT analysis
Figure 4.17: Effect of blade extensions on power output
Important features of variable length blade tidal turbine were revealed in Figure 4.16.
Power output is plotted (Figure 4.17) against tidal stream velocity for different blade
extensions. It is important to note that the tidal turbine was simulated at a range of tide
speeds while maintaining a fixed rotational speed. Lowest power extraction was observed
for minimum blade extension (10%) while highest power was obtained for maximum
extension. The reason behind such phenomenon is the increment in swept area with the
increase in blade length which is directly proportional to the power output (See Equation
2.2). Below the rated tide speed, for example at 1.5 ms-1, the power produced by the 40%
0
20
40
60
80
100
120
140
160
180
0 0.5 1 1.5 2 2.5
Pow
er, P
(kW
)
Velocity,U (m/s)
40% Extension30% Extension20% Extension10% ExtensionStandard HATT
72
extended turbine is approximately 79% more than that of the 10% extended blade.
Similarly, for 20% and 30% extended blades, 23% and 51% increase in power output is
determined respectively in comparison with the 10% extended blade.
As the model turbine that can extend blade length with the decrease in tide speed, thus
it is proficient to harness more energy than the baseline turbine. The power output
between the cut-in and cut-out speed of a tidal turbine with extensible blades was also
improved due to the increase of flow contact area.
4.3.2 Power prediction from CFD analysis
Figure 4.18: Power output for minimum and maximum extended model
The power output curves of the variable length blade HATT model at minimum and
maximum extended condition are presented in Figure 4.18. Similar to the BEMT results,
the power output was found to increase with blade extension. Although in CFD study, the
performance coefficients of the variable length blade HATT were observed to suffer due
0
20
40
60
80
100
120
140
0 0.5 1 1.5 2 2.5
Pow
er, P
(kW
)
Velocity, U (m/s)
73
to the presence of the step change in chord, a potential increment in the power output was
noticed. Therefore, the drop in power coefficient has minor impact to the power output
with the increment in swept area. Below the rated speed, the maximum extended blades
of the model turbine were able to produce approximately 72% more power than that
harnessed by the model at rated condition (Table 4.2). With the further decrease in tide
speed, the produced power was also greater but, the power harnessing capacity seemed to
be lowered in percentage. This is due to the increase in drag force dominance with the
decrease in tide speed for blades with larger swept area.
Table 4.2: Comparison of power capture at different tide speeds
Tide Speed Output Power (kW)
(m/s) Maximum Extended
Minimum Extended
% Increment
1.1 13.95508 12.33973 13.0906504
1.3 31.23805 20.44435 52.795562
1.5 57.53022 33.49097 71.7783136
1.7 80.88918 55.79813 44.9675357
2 127.6241 96.70562 31.971792
As the minimum extended model proved to act like the fixed bladed traditional turbine,
the CFD results also indicated that the model was able to harness more energy than the
standard HATT. Hence, use of the simple power control mechanism enabled the model
to operate efficiently not only at rated velocity but also at lower tidal velocities.
In addition, model seems to be used as an alternative to the sight specific turbines by
simply altering the blade length. The design cost associated with HATT is much high. In
such a way, it can be a substitute of the present tidal turbines.
74
CHAPTER 5: CONCLUSIONS & RECOMMENDATIONS FOR FUTURE
WORK
In this study, the variable length blade concept was investigated as an updated
technique to improve the efficiency of tidal turbine. This chapter summaries the research
work, followed by conclusion and finally, recommendations for further work.
5.1 Summary of the work
A variable length blade HATT was modelled to investigate on the non-dimensional
performance characteristics and associated power extraction via two-dimensional and
three-dimensional numerical simulation techniques.
For the present work, validation study of the simulation techniques was performed.
The three-bladed variable length blade HATT rotor was modelled from a baseline
standard HATT. The two-dimensional numerical simulations were conducted by an open
source software tool QBlade 0.8. All three-dimensional simulations have been executed
with the commercial CFD package ANSYS FLUENT 15.0 which is used as a three-
dimensional, segregated, implicit and incompressible flow solver. The three-dimensional
rotor models were developed, meshed and the computational domains were preprocessed
in GAMBIT 2.4.6.
k – ω SST turbulence model was used for CFD simulation. The mesh in the blade and
computational domain was refined by performing a grid independence study, adjusting
the global scale factor to obtain different mesh densities. In order to reduce computation
time and obtain reliable results, optimum mesh density and time step were selected for
model simulation from the grid and time dependence study.
In case of BEMT simulation, 10%, 20%, 30% and 40% tip blade extensions were
considered to study the blade extension effects on hydrodynamic performance of the
75
modelled HATT. However, for three-dimensional CFD analysis, the study was carried
out for maximum and minimum model blade extensions.
5.2 Conclusions
The study is concluded with the following remarks:
• Both the two-dimensional BEMT and three-dimensional CFD model results were
found to fit well with the existing research data in the validation study. Thus, we
can conclude that the simulation techniques used to predict the performance of the
variable length blade HATT model are reliable and might be applied further to
study performance of some other tidal turbines.
• In case of higher TSRs, all three non-dimensional performance coefficients of the
variable length blade HATT were improved as the blade extension varies from
lowest to highest. The power, torque and axial thrust coefficient values were
decreased with the increment in blade extensions at lower TSRs. Moreover, peak
CP value was dropped by 9% from CFD simulation which was due to the drag
force generated at the joint of tip and root blade section. In addition, non-
dimensional performance coefficients of the variable length blade HATT model
(with 10% blade extension) were found similar to the baseline HATT turbine at
the rated condition from both 2D and 3D simulations.
• Substantial gain in power output corresponding to the increase in swept area is
assured from both BEMT and CFD simulation results. Apart from the low peak
CP value, the power extraction was enhanced greatly throughout the operational
tide speeds with the increment of blade length. Power extraction percentage was
improved up to 72% compared with the minimum extended model as tidal stream
velocity reduced from 2 ms-1 to 1.5 ms-1. On the other hand, further decrease in
velocity was observed to reduce the model capacity of extracting power. At lower
76
tidal stream velocities, power extracted by the extended turbine blade was much
higher than the typical baseline HATT.
5.3 Recommendations for future work
• Experimental study on the performance of the scaled model variable length blade
HATT is essential to improve the research data from the present two-dimensional
and three-dimensional numerical simulations.
• Blade design can be optimized considering rotor radius, chord, twist and airfoil
distributions as design variables to ensure maximum energy harness by the HATT
with variable length blade.
• Study on the blade structure of variable length blade HATT such as impact of the
static load on blades might be carried out to confirm sufficient structural strength.
A well-matched coupling mechanism can be selected to provide variable length
blade feature which can efficiently operate at sea environment.
• As the variable length blade HATT model was found more proficient in energy
extraction compared with the typical HATTs, the turbine model can be
implemented commercially for electricity supply to national grid after prototype
test.
77
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LIST OF PUBLICATIONS AND PAPERS PRESENTED
Arzu, F., Darvishi, H. H., Hashim, R. B., Ghazvinei, P. T., & Soeb, M. R. (2016). Numerical investigation on the hydrodynamic performance of variable length blade tidal turbine: an attribute to enhance energy capture. IET Renewable Power Generation, 11(3), 347-352.
Soeb, M. R., Islam, A. S., Jumaat, M. Z., Huda, N., & Arzu, F. (2017). Response of nonlinear offshore spar platform under wave and current. Ocean Engineering, 144, 296-304.