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

ii

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:

iii

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.

iv

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.

v

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.

vi

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

viii

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

REFERENCES

Abbott, I. H., & Von Doenhoff, A. E. (1959). Theory of wing sections, including a summary of airfoil data. Mineola, NY, USA: Dover Publications Inc.

Afgan, I., McNaughton, J., Rolfo, S., Apsley, D. D., Stallard, T., & Stansby, P. (2013). Turbulent flow and loading on a tidal stream turbine by LES and RANS. International Journal of Heat and Fluid Flow, 43, 96-108.

Afjeh, A. A., & Keith, T. G. (1989). A simple computational method for performance prediction of tip-controlled horizontal axis wind turbines. Journal of Wind Engineering and Industrial Aerodynamics, 32(3), 231-245.

ANSYS (2010). FLUENT Theory Guide. ANSYS Academic Research Release 13. ANSYS Inc.

Bahaj, A.S., Batten, W.M.J., & McCann, G. (2007). Experimental verifications of numerical predictions for the hydrodynamic performance of horizontal axis marine current turbines. Renewable Energy, 32(15), 2479-2490.

Batten, W. M. J., Bahaj, A. S., Molland, A. F., & Chaplin, J. R. (2008). The prediction of the hydrodynamic performance of marine current turbines. Renewable energy, 33(5), 1085-1096.

Boyer M. (2013). World’s first floating wind-current turbine to be installed off Japanese coast [Online]. Retrieved 28 Jan, 2016, from https://inhabitat.com/worlds-first-floating-wind-current-turbine-to-be-installed-off-japanese-coast.

Buhl, M. L. (2005). A new empirical relationship between thrust coefficient and induction factor for the turbulent windmill state. (Technical Report No: NREL/TP-500-36834 TRN: US200516%%879) Golden, CO (USA): National Renewable Energy Laboratory.

Chong, H. Y., & Lam, W. H. (2013). Ocean renewable energy in Malaysia: The potential of the Straits of Malacca. Renewable and Sustainable Energy Reviews, 23, 169-178.

Clarke, J. A., Connor, G., Grant, A. D., & Johnstone, C. M. (2007). Design and testing of a contra-rotating tidal current turbine. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 221(A2), 171-179. doi: 10.1243/09576509JPE296

Clarke, J.A., Connor, G., Grant, A., Johnstone, C., & Ordonez-Sanchez, S. (2008, Oct). A Contra-rotating Marine Current Turbine on a Flexible Mooring: Development of a Scaled Prototype. Paper presented in the 2nd International Conference on Ocean Energy, Brest, France.

Clarke, J. A., Connor, G., Grant, A. D., Johnstone, C.M., & Ordonez-Sanchez, S.. (2010). Analysis of a single point tensioned mooring system for station keeping of a contra-rotating marine current turbine. IET Renewable Power Generation, 4(6), 473.

78

Dawson, M. H. (2006). Variable length wind turbine blade. (Final report, Energy Unlimited Inc. award number: DE-FG36e03GO13171). Retrieved from: http://www.osti.gov/energy citations/ servlets/purl/841190-OF8Frc/841190.PDF.

Dawson, M. H. (2009). Telescoping wind turbine blade. Washington, DC: U.S. Patent and Trademark Office.

Drela M. (1989) XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils. In: Mueller T.J. (Ed.) Low Reynolds Number Aerodynamics. Lecture Notes in Engineering, vol 54, (pp. 1-12). Verlag Berlin, Heidelberg: Springer.

Elghali, S. E. B., Balme, R., Le Saux, K., Benbouzid, M. E. H., Charpentier, J. F., & Hauville, F. (2007). A simulation model for the evaluation of the electrical power potential harnessed by a marine current turbine. IEEE Journal of Oceanic Engineering, 32(4), 786-797.

Eriksson, S., Bernhoff, H., & Leijon, M. (2008). Evaluation of different turbine concepts for wind power. Renewable and Sustainable Energy Reviews, 12(5), 1419-1434.

EMEC. (2012). Tidal Devices [Online]. Retrieved 14 April, 2015 from http://www.emec.org.uk/marine-energy/tidal-devices/

Fleming, C. F., McIntosh, S. C., & Willden, R. H. J. (2013, Sep). Tidal Turbine Performance in Sheared Flow. Paper presented at the 10th European Wave and Tidal Energy Conference. Aalborg, Denmark.

Flowers L.H. (2011, March 11). Savonius wind turbine. Message posted to http://love-heart-flowers.blogspot.com/2011/03/savonius-wind-turbine.html.

FLUENT, Inc. (2006). FLUENT 6.3 user’s guide. FLUENT documentation.

Flumill (2016). The Technology [Online]. Retrieved 10 Feb, 2016 from http://www.flumill.com/ The_Technology/content-1.html

Fraenkel, P. (2006). Tidal current energy technologies. Ibis, 148(s1), 145-151.

Fraenkel, P. (2010, Oct). Practical tidal turbine design considerations: a review of technical alternatives and key design decisions leading to the development of the SeaGen 1.2 MW tidal turbine. Paper presented at the Ocean Power Fluid Machinery Seminar. London, UK.

Fraenkel, P. (2014). Energy from tidal streams: engineering issues, state of the art and future prospects. Underwater Technology, 32(1), 27-37.

Frost, C. (2016). Flow Direction Effects On Tidal Stream Turbines (Doctoral dissertation, Cardiff University). Retrieved from https://ethos.bl.uk/OrderDetails.do? uin=uk.bl.ethos.709571.

Gant, S., & Stallard, T. (2008). Modelling a tidal turbine in unsteady flow. Proceedings of the Eighteenth International Offshore and Polar Engineering Conference

Cupertino, California, USA (pp. 473-480). California, USA: ISOPE

79

GE Wind Energy, L. L. C. (2006). Advanced Wind Turbine Program Next Generation Turbine Development Project: June 17, 1997--April 30, 2005 (No. NREL/SR-500-38752). National Renewable Energy Laboratory (NREL), Golden, CO.

Generation T. (2010). Product Development [Online]. Retrieved 20 Jan, 2012, from http://www.tidalgeneration.co.uk/products/

Goldin, D.S., Venneri, S.L., & Noor, A.K. (2001). Fresh air, wide-open space. Mechanical Engineering, 123(11), 48-55.

Goundar, J. N. & Ahmed M. R. (2013). Design of a horizontal axis tidal current turbine. Applied Energy, 111, 161-174.

Guney, M. S. (2011). Evaluation and measures to increase performance coefficient of hydrokinetic turbines. Renewable and Sustainable Energy Reviews, 15(8), 3669-3675.

Han, S. H., Park, J. S., Lee, K. S., Park, W. S., & Yi, J. H. (2013). Evaluation of vertical axis turbine characteristics for tidal current power plant based on in situ experiment. Ocean Engineering, 65, 83-89.

Hansen, M. O. L. (2008). Aerodynamics of wind turbines (2nd ed.). London, England: Earth scan.

Herring, H. (2006). Energy efficiency—a critical view. Energy, 31(1), 10-20.

Imraan, M., Sharma, R. N., & Flay, R. G. (2013). Wind tunnel testing of a wind turbine with telescopic blades: The influence of blade extension. Energy, 53, 22-32.

Jaber, J. O., Badran, O. O., & Abu-Shikhah, N. (2004). Sustainable energy and environmental impact: role of renewables as clean and secure source of energy for the 21st century in Jordan. Clean Technologies and Environmental Policy, 6(3), 174-186.

Jo, C. H., Lee, J. H., Kim, D. Y., Lee, K. H. (2013, Sep). Performance of a Horizontal Axis Tidal Current Turbine with Blade Deformation. Paper presented at the 10th European Wave and Tidal Energy Conference, Aalborg, Denmark.

Jones, J. A., & Chao, Y. (2009, Jun). Offshore hydrokinetic energy conversion for onshore power generation. Paper presented at the ASME 28th International Conference on Ocean, Offshore and Arctic Engineering, Honolulu, Hawaii.

Khan, M. J., Bhuyan, G., Iqbal, M. T., & Quaicoe, J. E. (2009). Hydrokinetic energy conversion systems and assessment of horizontal and vertical axis turbines for river and tidal applications: A technology status review. Applied Energy, 86(10), 1823-1835.

Kiho, S., Shiono, M., & Suzuki, K. (1996). The power generation from tidal currents by Darrieus turbine. Renewable Energy, 9(1), 1242-1245.

80

Koh, S. L., & Lim, Y. S. (2010). Meeting energy demand in a developing economy without damaging the environment— A case study in Sabah, Malaysia, from technical, environmental and economic perspectives. Energy Policy, 38(8), 4719-4728.

Kirke, B. (2005). Developments in ducted water current turbines [Online]. Retrieved 27 Jun, 2016 from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.531. 3501&rep=rep1&type=pdf.

Lam, W. H., & Bhatia, A. (2013). Folding tidal turbine as an innovative concept toward the new era of turbines. Renewable and Sustainable Energy Reviews, 28, 463-473.

Larcher, D., & Tarascon, J. M. (2015). Towards greener and more sustainable batteries for electrical energy storage. Nature chemistry, 7(1), 19-29.

Lee, J. H., Kim, D. H., Rhee, S. H., Do, I. R., Shin, B. C., & Kim, M. C. (2011, Jun). Computational and experimental analysis for horizontal axis marine current turbine design. Paper presented in Second International Symposium on Marine Propulsors, Hamburg, Germany.

Lee, J. H., Park, S., Kim, D. H., Rhee, S. H., & Kim, M. C. (2012). Computational methods for performance analysis of horizontal axis tidal stream turbines. Applied Energy, 98, 512-523.

Lim, Y. S., & Koh, S. L. (2010). Analytical assessments on the potential of harnessing tidal currents for electricity generation in Malaysia. Renewable Energy, 35(5), 1024-1032.

Low, M. (2012). Creating a balanced energy mix in Southeast Asia Energy Studies [Online]. Singapore international energy week. Retrieved from http://esi.nus.edu.sg/public-ations/2012/06/14/creating-a-balanced-energy-mix-in-southeast-asia

Macnaughton, D. Fraenkel, P.L., Paish, O.F., Hunter, R., & Derrick, A. (1993). Tidal stream turbine development. Paper presented at the International Conference on Renewable Energy-Clean Power 2001, London, UK.

Malki, R., Williams, A.J., Croft, T.N., Togneri, M., & Masters, I. (2013). A coupled blade element momentum–Computational fluid dynamics model for evaluating tidal stream turbine performance. Applied Mathematical Modelling, 37(5), 3006-3020.

Marten, D., Wendler, J., Pechlivanoglou, G., Nayeri, C.N., & Paschereit, C.O. (2013). QBLADE: an open source tool for design and simulation of horizontal and vertical axis wind turbines. International Journal of Emerging Technologies and Advanced Engineering, 3(3), 264-269.

Mason-Jones, A. (2010). Performance assessment of a horizontal axis tidal turbine in a high velocity shear environment (Doctoral dissertation). Available from ProQuest Dissertations & Theses database (UMI No. U585299).

81

Mason-Jones, A., Evans, P. S., O'Doherty, T., & O'Doherty, D. M. (2008, Jul). Characterisation of a tidal stream turbine design using CFD and ADCP. Paper presented at the World Renewable Energy Conference, Glasgow, UK.

Masters, I., Chapman, J. C., Willis, M. R., & Orme, J. A. C. (2011). A robust blade element momentum theory model for tidal stream turbines including tip and hub loss corrections. Journal of Marine Engineering & Technology, 10(1), 25-35.

McCoy, T., & Griffin, D. (2006, Jan). Active control of rotor aerodynamics and geometry: statues, methods, and preliminary results. Paper presented at the 44th AIAA Aerospace Science Meeting and Exhibit, Reno, Nevada.

McSherry, R., Grimwade, J., Jones, I., Mathias, S., Wells, A., & Mateus, A. (2011, Sep). 3D CFD modelling of tidal turbine performance with validation against laboratory experiments. Paper presented at the 9th European Wave and Tidal Energy Conference, Southampton, UK.

Michelen, C., Neary, V. S., Murray, J., & Barone, M. F. (2014). Cactus open source code for hydrokinetic turbine design and analysis: model performance evaluation and public dissemination as open source design tool (No. SAND2014-3560C). Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States).

Minesto. (2015). Deep Green Technology [Online]. Retrieved 25 Jan, 2016, from http://minesto.com/deep-green/

Mirzaei, A., Tangang, F., & Juneng, L. (2014). Wave energy potential along the east coast of Peninsular Malaysia. Energy, 68, 722-734.

Molland, A. F., Bahaj, A. S., Chaplin, J. R., & Batten, W. M. J. (2004). Measurements and predictions of forces, pressures and cavitation on 2-D sections suitable for marine current turbines. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 218(2), 127-138. doi: 10.1243/1475090041651412.

Molland, A. F., & Turnock, S. R. (2011). Marine rudders and control surfaces: principles, data, design and applications. Oxford, England: Butterworth-Heinemann.

Nicholls-Lee, R. F. (2011). Adaptive composite blades for horizontal axis tidal turbines (Doctoral dissertation, University of Southampton). Retrieved from https://eprints.soton.ac.uk/209357.

Nicholls-Lee, R. F., & Turnock, S. R. (2007). Enhancing performance of a horizontal axis tidal turbine using adaptive blades. Proceedings of OCEANS 2007-Europe, 1-6. doi: 10.1109/OCEANSE.2007.4302437

Nicholls-Lee, R. F., & Turnock, S. R. (2008). Tidal energy extraction: renewable, sustainable and predictable. Science progress, 91(1), 81-111.

82

Ölz, S., & Beerepoot, M. (2010). Deploying Renewables in Southeast Asia: Trends and potentials (No. 2010/6). OECD Publishing.

OpenHydro. (2012). Technology [Online] Retrieved 4 Feb 2016, from http://www.openhydro.com/news/100908.html

Orme, J.A.C., Masters, I., & Mima, C. (2006, Mar). Analysis and comparison of support structure concepts for tidal stream turbines. Paper presented at the World Maritime Technology Conference, IMarEST: London, UK.

Pasupulati, S. V., Wallace, J., & Dawson, M. (2005, June). Variable length blades wind turbine. Proceedings of Power Engineering Society General Meeting, 2097-2100. doi: 10.1109/PES.2005.1489577

Perier, C. (2007, Sep). The Rance Tidal Power Plant. Paper presented at the Wave and Tidal Technology Symposium, Renewable Energy Association, Cowes, Isle of Wight, U.K.

Power, V. (2015). Kinetic Hydropower System (KHPS) [Online]. Retrieved 21 Dec, 2015, from http://www.verdantpower.com/kinetic-hydropower-system.html

Quirapas, M. A. J. R., Lin, H., Abundo, M. L. S., Brahim, S., & Santos, D. (2015). Ocean renewable energy in Southeast Asia: A review. Renewable and Sustainable Energy Reviews, 41, 799-817.

Roach, J. (2003). Underwater Windmill Helps Power Arctic Village. National Geographic News, October.

Rourke, F. O., Boyle, F., & Reynolds, A. (2010). Marine current energy devices: current status and possible future applications in Ireland. Renewable and Sustainable Energy Reviews, 14(3), 1026-1036.

Sharma, R. N., & Madawala, U. K. (2012). The concept of a smart wind turbine system. Renewable energy, 39(1), 403-410.

Shen, W. Z., Mikkelsen, R., Sørensen, J. N., & Bak, C. (2005). Tip loss corrections for wind turbine computations. Wind Energy, 8(4), 457-475.

SMD (2016). Products [Online]. Retrieved 16th Jan, 2016, from http://www.smd.co.uk/products/marine-renewables/special-projects.htm

Snel, H., Houwink, R., Bosschers, J., Piers, W. J., Van Bussel, G. J. W., & Bruining, A. (1993). Sectional prediction of 3-D effects for stalled flow on rotating blades and comparison with measurements. Netherlands Energy Research Foundation ECN.

Snodin, H. (2001). Scotland’s renewable resource, volume I: the analysis: Tech. Rep. Garrand Hassan and Partners Limited.

Song, M., Kim, M. C., Do, I. R., Rhee, S. H., Lee, J. H., & Hyun, B. S. (2012). Numerical and experimental investigation on the performance of three newly designed 100

83

kW-class tidal current turbines. International Journal of Naval Architecture and Ocean Engineering, 4(3), 241-255.

STEC (2013). National Energy Balance 2011[Online]. Putrajaya, Malaysia: Suruhanjaya Tenaga (Energy Commission). Retrieved from http://meih.st.gov.my/documents/ 10620/6ee119f3-8bcf-4a7b930eae375dbbc544

STEC (2015). Malaysia Energy Statistics Handbook 2015 [Online]. Suruhanjaya Tenaga

(Energy Commission). Putrajaya, Malaysia. Retrieved from http://meih.st.gov.my/documents/10620/f3b9119e-e139-4527-9da6d77e2eab1c34.

Systems, BP. (2013). bioStream [Online]. Retrieved 25 Dec, 2015, from http://www.biopowersystems.com/biostream.htm

Taylor, P., (2007). SeaGen Tidal Power Installation [Online] Retrieved 20 Dec, 2015, from http://www.alternative-energy-news.info/seagen-tidal-power-installation.

Tidalsails. (2013). Tidalsails. Retrieved 10 Feb, 2016, from http://tidalsails.com/about-us/

UK, R. (2011). Wave and Tidal Energy in the UK. Retrieved 20 Feb, 2015 from http://www.bwea.com/pdf/marine/Wave-Tidal_energy_UK

Viterna, L. A., & Corrigan, R. D. (1982). Fixed pitch rotor performance of large horizontal axis wind turbines. Large Horizontal-Axis Wind Turbines, 1, 69-85.

VerdErg. (2013). Spectral Marine Energy Converter. Imperial Engineer Magazine.

Wiratama, I. K. (2012). Aerodynamic Design of Wind Turbine Blades Utilising Nonconventional Control Systems (Doctoral dissertation, Northumbria University).

Yaakob, O. (2013, Feb). Marine renewable energy initiatives in Malaysia. Paper presented at the Southeast Asian Collaboration for Ocean Renewable Energy,

Nanyang Ave, Singapore.

Yaakob, O., Ab Rashid, T. T., & Mukti, M. A. (2006). Prospects for ocean energy in Malaysia. Proceedings of International Conference on Energy and Environmental (ICEE), Universiti Tenaga Nasional, Kuala Lumpur, Malaysia (pp. 62-68). Kuala Lumpur, Malaysia: Universiti Tenaga Nasional.

Yuce, M. I., & Muratoglu, A. (2015). Hydrokinetic energy conversion systems: a technology status review. Renewable and Sustainable Energy Reviews, 43, 72-82.

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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.