1

Hydropower for sustainable development:

CFD modelling and hydro-mechanical behavior of micro hydro converters for pressure flow

Roberta Zimmitti, roberta.zimmitti@gmail.com

Instituto Superior Técnico, Lisboa, Portugal.

June 2016

KEYWORDS: Hydraulic turbine, CFD modelling, micro-hydro, tubular propeller, series turbine.

ABSTRACT: This paper aims at examining the hydropower plants to produce electrical energy and analyzing the behavior

of the tubular propeller in pressurized pipe. Hydropower plants are one of the most used energy sources. So far the hydro-

power plants involved mainly huge water discharge, therefore huge electric power production. For these types of power

plants, the water turbines are really developed; it is showed a briefly explanation of the basic physics principle of these

hydraulic machines. However, in the last few years micro-hydropower scheme has been deeply investigated in order to be

able to generate energy from small rivers. The turbine technology for this new type of plant schemes are almost unexplored.

The tubular propeller turbine is one of the most used machine in the micro-power plants. It is presented the CFD analysis

of five and three blade propeller inside a pressurized pipe. Additionally, I analyzed the CFD model of the innovative solution

of series turbine. Two five blade tubular propeller are installed inside a pressurized pipe to generate energy.

1. INTRODUCTION

The majority of the electricity generated in the world today

comes from fossil fuel. Conventional energy sources based

on oil, coal, and natural gas have proven to be highly effec-

tive drivers of economic progress, but at the same time

damaging to the environment and to human health. These

traditional fossil fuel-based energy sources are facing in-

creasing pressure on a host of environmental fronts, with

perhaps the most serious challenge confronting the future

use of coal being the Kyoto Protocol greenhouse gas (GHG)

reduction targets.

Figure 1 - World net electricity generation by fuel, 2010-2040 (Source: Key World Energy Statistics 2015, IEA)

The renewable energy sources currently supply between

15% and 20% of world’s total energy demand. The potential

of renewable energy sources (RES) is enormous; biomass,

wind, solar, hydropower, and geothermal can provide sus-

tainable energy services, based on the use of routinely

available, indigenous resources. A transition to renewa-

bles-based energy systems is looking increasingly in the

past 30 years and continue to rise.

Figure 2 - Historic contribution from RES (Source: EEA)

Hydropower is the largest renewable resource used for

electricity. Since latest 19th century it became a source for

generating electricity. Nowadays, it plays an essential role

in many regions of the world, especially to supply villages

2

and local communities off-grid, such as many poor areas of

Africa or Asia.

2. HYDROPOWER PLANT

Hydropower continues to be the most efficient way to gen-

erate electricity. Hydropower continues to be one of the

most efficient way to generate electricity. Modern hydro

turbines can convert as much as 90% of the available energy

into electricity.

Basically, there are four types of hydroelectric power

plants:

Conventional plant is the most widespread hydro-

power plant. Water released from the reservoir flows

through one or more turbines, which in turn activates

a generator to produce electricity.

Pumped-storage is a type of hydroelectric energy

storage used by electric power systems for load bal-

ancing. Pumped-storage hydropower (PSH) is used to

capture off-peak power and release it at times of high

demand. Off-peak electricity is used to pump water

from the lower to the higher reservoir, turning elec-

trical energy into gravitational potential energy.

When electricity is needed, water is released back

down to the lower reservoir, spinning a turbine and

generating electricity. PSH accounts for more than

99% of bulk storage capacity worldwide: around

127,000MW, according to the Electric Power Research

Institute (EPRI).

Run-of-the-river hydroelectric stations are those with

small or no reservoir capacity, so that only the water

coming from upstream is available for generation at

that moment.

Tidal power is a form of hydropower that converts the

energy obtained from tides into useful forms of

power.

Small-scale micro hydro power is both an efficient and re-

liable form of energy. Small hydropower can be classified

in mini, micro or pico, depending on the output power and

on the type of the adopted scheme. There are not yet glob-

ally accepted boundaries to define these classes, but micro-

hydro typically refers to schemes below 100 kW, while

pico-hydro usually produces less than 5 kW. Micro hydro

systems can generate a large amount of energy out of a

small water flow with minimal impact. These systems can

generate enough energy to recharge batteries, providing

energy in off-grid communities.

Hydro-electric systems can be divided into four configura-

tions:

On-grid without batteries: This a simple and efficient

system that sends any surplus energy back into the

grid.

On-grid with batteries: This system type also sells

back surplus electricity, but also provides backup

during utility outages.

Off-grid without batteries: This configuration is gen-

erally for larger, AC-generating systems. This config-

uration is generally not used for systems that generate

at less than about 2 kW.

Off-grid with batteries: This is the most common off-

grid option, and is similar to off-grid solar- or wind-

electric systems. The charging source puts energy

into a battery bank, while loads are run from the bat-

teries directly.

A typical hydropower plant scheme consists of several

components, such as: reservoir (or dam), intake conduit,

the penstock, the surge tank and the power house. The

purpose of the power house is to support and protect from

the environment the hydraulic machines and the genera-

tors.

2.1 HIDRAULIC TURBINE

Hydraulic turbines may be defined as prime movers that

transform the kinetic energy of the falling water into me-

chanical energy of rotation and whose primary function is

to drive the electric generator.

The turbine is the main component of the plant. It converts

the potential and kinetic energy of the water into mechan-

ical energy. As much as the turbine is well projected for the

specific purpose, as efficiency is high,

So far the modern hydro turbines can convert as much as

90% of the available energy into electricity.

Hydraulic turbines are generally classified as:

Impulse turbines which operate by accelerating and

changing the flow direction through a station-

ary nozzle (the stator blade) onto the rotor blade.

In a reaction turbine the nozzles that discharge the

fluid are attached to the rotor. The acceleration of the

fluid produces a reaction force, causing the rotor to

move in the opposite direction. Then the energy

transfered is due to two mechanisms: the drop in

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pressure from the inlet to the outlet of the runner; the

change in directions of the flow velocity.

Figure 3 - Comparison between impulse and reaction turbine configura-

tion

Hydroelectric plants utilize the energy of water falling

through a head that may vary from a few meters to 2000 m.

To manage this wide range of heads, many different kinds

of turbines are employed, which differ in their working

components. The selection is based on the available water

head. Hydraulic head is usually divided into three catego-

ries: low, medium, and high head. In general, impulse tur-

bines are used for high head sites, and reaction turbines are

used for low head sites.

Type of turbine Hydraulic head [m]

Aproximate Specific Speed

Pelton impulse 50 to 1300 4

Turgo impulse 50 to 250 7 to 15

Francis reaction 40 to 600 15 to 100

Kaplan reaction 10 to 70 100 to 200

Table 1 - Hydraulic turbines overview

The electric power produced vary with the available hy-

draulic head and the flow rate. It can roughly be compute

as:

𝑃𝑒 = 𝜂𝑡𝜌𝑔𝑄𝐻𝑛

Where ηt is the total efficiency of the turbine; Q is the flow

rate [m3/s]; Hn is the net head [m], it can be computed as:

𝐻𝑛 = 𝐻𝑡 − ∆ℎ𝑙𝑠

Where Ht is the total head; Δhls are the hydraulic loss be-

tween the higher reservoir and the lower reservoir after the

turbine. They are the sum of the local head losses (hl) and

the friction head losses (hf).

Friction loss, or distributed loss, is due to the shear

stress between the pipe surface and the fluid flowing

within. It depends on the conditions of flow (laminar or

turbulent flow) and the physical properties of the system.

These conditions can be encapsulated into a dimensionless

number, Reynolds number:

𝑅𝑒 = 𝜌 𝑉 𝐷

𝜇

Where V is the mean velocity of the fluid [m/s]; D is the

diameter of the pipe [m]; μ is the dynamic viscosity of the

fluid [kg/ m s].

Some of the empirical relation to compute the friction

losses are tabulated below:

Flow Relation

Hagen-Poiseuille laminar ℎ𝑓 = 8 𝜇 𝐿 𝑄

𝜋𝜌𝑔𝑅4

Darcy-Weisbach laminar 𝑓𝐷 = 64

𝑅𝑒

Blasius turbulent 𝑓 = 0,316

𝑅𝑒0,25

Hanzen-Williams turbulent ℎ𝑓 = 6.78 𝐿

𝐷1.165 (𝑉

𝐶)

1.85

Table 2 - Friction loss relations

The local losses may raise to pipe entrance or exit, sudden

or gradual expansion or contraction, bends, elbows, tees,

and valves. The most common relation used to compute

the local head losses is:

ℎ𝑙 = 𝐾𝐿

𝑉2

2𝑔

Where V is the mean velocity of the fluid [m/s]; KL is the

local loss coefficient. It is tabulated for the most common

pipe components.

3. SIMILARITY LAWS

With the application of dimensional analysis and similar-

ity or affinity laws, the number of experiments can be sig-

nificantly reduced. Performance of the prototype can be

predicted from tests, then with the similarity laws, the re-

sults obtained from experiments done with scaled turbine

can be used to project real scale turbine. There are three

similarity conditions:

Geometric similarity - The prototype is the same

shape as the real application. Therefore, the linear di-

mension ratio of two geometrically similar turbines

are the equal.

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Kinematic similarity - Two turbines that work under

kinematic similarity have the same velocity triangles;

thus fluid streamlines are similar.

Dynamic similarity - Geometric and similarity forces.

Therefore, the ratios between different forces in real

scale model must be the same in model scale. Hence

the model scale and the real scale operate under equal

conditions and efficiencies.

For two machines geometrically similar, if it is considered

that there is a kinematic and dynamic similarity between

them, exclusively if the efficiency is the same, the following

relation is valid:

𝑛∗

𝑛= (

𝑄

𝑄∗)

1/2

(𝐻∗

𝐻)

3/4

= ( 𝑃

𝑃∗)

1/2

(𝐻∗

𝐻)

5/4

Where n is the rotational speed [rpm]; Q is the volumetric

flow rate [m3/s]; P is the net power produced [W]; H is the

net head at which the turbine works [m].

In these relation the terms with the star (*) corresponds to

the values of the real model; the terms without the star are

the values of the scaled prototype.

4. HYDRO-MECHANIC BEHAVIOUR

In general, there are wide ranges of material mechanical

degradation mechanisms. Basically, most of the damage in

water turbine are due to cavitation phenomenon and ero-

sive and abrasive mechanism.

4.1 CAVITATION PHENOMENON

Cavitation occurs when the liquid pressure is reduced to

the vapour pressure of the liquid; when this occurs, vapour

bubbles form. These vapour bubbles collapse when they

reach the blades inside the machines, which is under a high

pressure. These pressures are so high that they cause pit-

ting of metal and consequently decrease the life and effi-

ciency of the turbomachinery. Turbines show declined per-

formance after few years of operation. Thus, the manage-

ment of cavitation is really important in small hydropower

plants for achieving higher efficiency.

For proper turbine operation, it must be:

𝑁𝑃𝑆𝐻𝐴 ≥ 𝑁𝑃𝑆𝐻𝑅

Where NPSHA in the Net Positive Suction Head available

in the system; NPSHR is the Net Positive Suction Head re-

quired so cavitation will not occur.

For a specific water turbine, the NPSHA can be evaluated

as:

𝑁𝑃𝑆𝐻 = 𝐻𝑐 − 𝑧

Where z is the turbine vertical height (m) and Hc is the

vacuum head (m). The vacuum head, at which cavitation

will commence, is defined by the equation:

𝐻𝑐 = 𝑝𝑎𝑡𝑚 − 𝑝𝑣

𝜌𝑔

Thomas parameter σth relates NPSH to turbine head(Ht):

𝜎𝑡ℎ = 𝑁𝑃𝑆𝐻

𝐻𝑡

To avoid the cavitation:

𝜎𝑡ℎ > 𝜎𝑐𝑟𝑖𝑡

The values of the critical Thoma coefficient are obtained

experimentally.

4.2 ABRASIVE AND EROSIVE MECHANISM

The dynamic action of sediment flowing along with water

that impact against a solid surface cause micro hole into

the blades.

Abrasive wear is the loss of material by the passage of

hard particles over a surface. This mechanism occurs

whenever a solid object is loaded against particles of a

material that have equal or greater hardness.

Erosive wear is caused by the impact of solid and liq-

uid particles on the surface of the blades. Erosive wear

can resemble abrasive wear when hard solid particles of

microscopically visible size are eroding agent.

Computational fluid dynamics (CFD) methods are em-

ployed to analyse the mechanics of hydro-abrasive and ero-

sive mechanism.

However, there is an empirical relation proposed by Zu-

Yan to roughly evaluate the abrasive/erosive damage risk.

The formulation involves the factor H*C, where H is the

net head of the turbine; C is the average annual particle

concentration in g/l of all particles with a diameter of > 50

µm.

The ranges for the Zu-Yan parameter are three:

H*C ≥ 7 the damage risk is severe;

0.7 < H*C < 7 the damage risk is moderate;

H*C ≤ 0.7 the damage risk is negligible.

It is also possible to slightly modify this factor to obtain a

more refined solution. The modification was proposed by

5

Nozaki. He proposes to modify the particle concentration

factor in order to relate it to the particle size, hardness,

shape, and runner material:

𝑃𝐸 = 𝑃 ∗ 𝑎 ∗ 𝑘1 ∗ 𝑘2 ∗ 𝑘3

Where PE is the modified suspended concentration; P is

the measured suspended concentration; factors a, k1, k2,

and k3 depend on the type and geometry of the particles

and type of runner material.

The final value is then used in curves of PE against turbine

net head to predict times between maintenance.

Figure 4 - Modify suspended concentration against turbine net head

5. CFD MODELLING

Nowadays CFD analysis play an important role to optimize

the production of energy in a hydropower plant. It is essen-

tial that the behaviour of the propeller is well known, then

it is possible to design the best propeller for that specific

situation.

5.1 INTRODUCTION

I have analised the CFD simulations of a tubular propeller

inside a pressurized pipe. I have made the simulations for

three and five blade tubular propeller, in order to compare

the different results obtained. Finally, I have studied the

innovative solution of series turbine.

The mathematical model used to solve this problem is the

Reynolds averaged Navier-Stokes equation (or RANS equa-

tion). The objective of the turbulence models for the RANS

equations is to compute the Reynolds stresses, which it is

done with the k-ε model; where k is the turbulent kinetic

energy and ε is the dissipation rate of turbulence energy.

The equations that describe this model are:

For the turbulent kinetic energy, k:

𝜕

𝜕𝑡(𝜌𝑘) +

𝜕

𝜕𝑥𝑖

(𝜌𝑘𝑢𝑖) = 𝜕

𝜕𝑥𝑗[(𝜇 +

𝜇𝑡

𝜎𝑘)

𝜕𝑘

𝜕𝑥𝑗]

+ 𝑃𝑘 + 𝑃𝑏 − 𝜌𝜀 − 𝑌𝑀 + 𝑆𝑘

For the dissipation rate, ε:

𝜕

𝜕𝑡(𝜌𝜀) +

𝜕

𝜕𝑥𝑖

(𝜌𝜀𝑢𝑖) = 𝜕

𝜕𝑥𝑗[(𝜇 +

𝜇𝑡

𝜎𝜀)

𝜕𝜀

𝜕𝑥𝑗]

+ 𝐶1𝜀

𝜀

𝑘(𝑃𝑘 + 𝐶3𝜀 𝑃𝑏) − 𝐶2𝜀 𝜌

𝜀2

𝑘+ 𝑆𝜀

Where u is the velocity component in the i direction; μt

represents the eddies viscosity: 𝜇𝑡 = 𝜌 𝐶𝜇𝑘2

𝜀, Cμ is a con-

stant; Pk is defined ad 𝑃𝑘 = 𝜇𝑡𝑆2, S is the modulus of the

mean rate of strain tensor: 𝑆 = √2 𝑆𝑖𝑗𝑆𝑗𝑖 ; Pb introduce the

effect of buoyancy: 𝑃𝑏 = 𝛽 𝑔𝑖 𝜇𝑡

𝑃𝑟𝑡

𝜕𝑇

𝜕𝑥𝑖, Prt is the turbulent

Prandtl Number, for standard model the value of Prt is as-

sumed 0.85; g if the component of gravitational vector in

the i direction; β is the coefficient of thermal expansion:

𝛽 = − 1

𝜌(

𝜕𝜌

𝜕𝑇)

𝑝. Model constants: C1ε=1.44; C2ε=1.92;

Cμ=0.09; C3ε=-0.33; σk=1.0; σε=1.3.

It is important to make a note of the assumptions that limit

these models: ideal lossless turbine; neglecting the elastic-

ity of the conduit system and the friction and the concen-

trated losses in the pipe; incompressible flow; turbulence

in equilibrium in boundary layers; assuming the water

properties at 293.15 K;

The results obtained will be slightly different from the real

case, but they are suitable for an accurate study of the in-

teraction between hydraulic machine and fluid.

5.2 MODEL DESCRIPTION

The geometry of the models is imported from Autodesk

AutoCAD; it consists in two domains, as the following pic-

ture shows.

Figure 5 - Model domains

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Domain 1 consists of the water inside the pipe minus

the domain 2 and the volume of the shaft. To simplify

the analysis, I create only the inside wall of the pipe;

then there is not the thickness of the pipe. For this

reason, the two domains are filled up with water.

The Domain 2 consists of the small cylinder empty of

the turbine’s volume. This is the rotating domain.

Under Rotating Machinery, Turbulent Flow, k-ε section I

have added the boundary condition to solve the problem,

clearly they depend on the simulations. Basically, I have

imposed: the rotation velocity for the rotating domain; the

velocity in the inlet section; the pressure in the outlet sec-

tion; and the flow continuity between the two domains.

6. ANALYSIS AND RESULTS

In this last section, I presented the results of the CFD sim-

ulations. The main parameters of the models are: the flow

rate Q [m3/h]; the pressure head H [mWc]; the rotational

speed ω [rpm]. Starting from the experimental results of

the same 5 blade tubular turbine, I have chosen to fix the

flow rate and the pressure head. As the following graph

shows, the best efficiency point is for a flow rate of 16 m3/h.

I have made several test for each turbine configuration

changing the rotation speed, specifically:

3BT – Fixing the flow rate and the outlet pressure, I

have run this model using five different rotation

speed: 250, 500, 750, 1000 and 1500 rpm.

5BT – Since from the analysis of the experimental re-

sults it is clear that the maximum efficiency is reached

around 750 rpm and 1000 rpm, I have made the sim-

ulations for these two values of rotation speed.

Series-5BT – I have obtained the simulation for four

simulations: for a flow rate of 16 m3/h with and for a

32 m3/h; in both cases I analyse the model for two ro-

tational speeds, 750 rpm and 1000 rpm.

I have studied all the models for time dependent solutions;

therefore, I have chosen to study the fluid behaviour inside

the pipe between zero and two and half second.

Here I present some solutions I obtained with COMSOL

Multiphysics, when the turbine run with a rotation speed

of 750 rpm.

6.1 3BT and 5BT RESULTS

The following picture show the velocity field inside the

pipe with three and five blades turbine.

Figure 6 - 3BT Velocity Field (Time step 2 s)

Figure 7 - 5BT Velocity Field (Time step 2 s)

It is clear that the velocity is highest around the turbine and it

is also evident that the velocity magnitude between the two

models is quite different. In the 3BT model the velocity reach

a lower value than the 5BT model. The average velocity mag-

nitude, after 2 seconds, in the rotating domain are: 0.85 m/s

in the 5BT model and 0.75 m/s in the 3BT. While, the maxi-

mum magnitude velocity values are: 3.47 m/s in the 5BT model

and 3.23 m/s in the 3BT.

Moreover, exactly as we expected, the region where the

vorticity reaches the highest values, is around the turbine.

The following figures show that the intensity of turbulence

is much stronger around the turbine blades but also

around the shaft and in the bend of the pipe.

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Figure 8 - 3BT Vorticity Field (Time step 2 s)

Figure 9 - 5BT Vorticity Field (Time step 2 s)

Since the turbulent kinetic energy is computed as 1

2(𝑢′2 + 𝑣′2 + 𝑤′2), as we expected the highest values of the

TKE and dissipation rate are reached in the same points

where the velocity has the maximum values; and properly,

in the second simulations turbulent kinetic energy devel-

oper around the blade, is much higher than the first simu-

lation.

Figure 10 - 3BT turbulent kinetic energy (Time step 2 s)

Figure 11 - 5BT turbulent kinetic energy (Time step 2 s)

6.2 SERIES-5BT RESULTS

Regarding the series turbine analysis, I present the compari-son between two flow rate and two imposed outlet pressure.

It is evident from the following graphs the velocity reaches

different values in the two models. Because of the dis-

charge increase, since the cross section of the pipe is con-

stant, then the velocity increase (V=Q/A). Therefore, re-

spectively the second picture shows a velocity field with

higher values, especially around the blades of the turbine.

Regarding the direction of the velocity vector, we can verify

that it is the same in both simulations. The stream lines

follow the same direction in both pictures.

Figure 12 - Series-5BT Velocity Field (Q=0.0044m3/s, pout=0.34 bar)

8

Figure 13 - Series-5BT Velocity Field (Q=0.0089m3/s, pout=0.20 bar)

The same consideration is true for the vorticity field.

Figure 14 - Series-5BT Vorticity Field (Q=0.0044m3/s, pout=0.34 bar)

Figure 15 - Series-5BT Vorticity Field (Q=0.0089m3/s, pout=0.20 bar)

6.3 EFFICIENCY RESULTS

To compute the efficiency, I have used the following equa-

tions:

𝜂 = 𝑃𝑚𝑒𝑐

𝑃ℎ

Where Pmec is the mechanical power and Ph is the hydraulic

power.

The following graphs show the trend of the efficiency

against the rotational speed. Afterwards the corresponding

values on the tables.

Figure 16 - 3BT Efficiency

n

[rpm]

H

[mWc]

Torque

[Nm]

Pm

[W]

Ph

[W]

η

[%]

250 0,24 0,139 3,65 9,35 35,27

500 0,24 0,069 3,62 10,35 35,02

750 0,23 0,038 2,97 9,91 29,92

Table 3 - 3BT Efficiency

Figure 17 - 5BT Efficiency

67,22%62,62%

45,53%

31,96%

0,00

0,20

0,40

0,60

0,80

500 750 1000 1250 1500 1750

Rotation Speed [rpm]

5BT Efficiency

9

The simulations have showed that the best efficiency point

is reached using the five blade turbine, 67% for a rotational

speed of 750 rpm.

In general, the power developed from these turbine model is

not remarkable, but it is due to the small dimension of the

turbine so the small flow rate.

Regarding the series turbine, I have used the same relations

of single turbine. The following tables show the results ob-

tained.

It is clear from the following tables, that the efficiency of the

turbine remains quite constant for single and series turbine.

Moreover, we can notice that in the first case, with a rate

flow of 16 m3/s and an outlet pressure of 0.34 bar, the effi-

ciencies are a little bit higher.

Discharge flow of 16 m3/h

Discharge flow of 32 m3/h

6.4 AFFINITY LAW ANALYSIS

Clearly from the tables above, the mechanical power devel-

oped from the turbine is quite low. Mainly this happen be-

cause the diameter of the turbine it is not big in size and

the flow rate is modest. To expand this results to different

turbine size, it is possible to apply the affinity laws, for dif-

ferent values od turbine diameters and flow rate.

Therefore, using the following equations, I analyse the

changing of developed mechanical power for a 5 blades

turbine with two different diameter and flow rate

𝑄 = 𝑄∗𝑁

𝑁∗(

𝐷

𝐷∗)

3

𝐻 = 𝐻∗ (𝑁

𝑁∗)

2

(𝐷

𝐷∗)

2

𝑃𝑚 = 𝑃𝑚∗ (

𝑁

𝑁∗)

3

(𝐷

𝐷∗)

5

Case 1: Diameter of 200 mm and flow rate of 37.27

m3/h

Table 4 - 5BT Efficiency

Turbine 1

n

[rpm]

H

[mWc]

Torque [Nm]

Pm

[W]

Ph

[W]

η

[%]

750 0,39 0,14 11,30 16,82 67,22

1000 0,38 0,10 10,47 16,39 63,88

Turbine 2

n

[rpm]

H

[mWc]

Torque [Nm]

Pm

[W]

Ph

[W]

η

[%]

750 0,4 0,14 10,68 17,25 61,90

1000 0,39 0,10 10,05 16,82 59,75

Table 5 - Series-5BT Efficiency (Q=16m3/s)

n

[rpm]

H

[mWc]

Torque

[Nm]

Pm

[W]

Ph

[W]

η

[%]

750 0,39 0,144 1,30 16,81 67,22

1000 0,38 0,098 10,26 16,39 62,62

1250 0,32 0,060 6,32 13,80 45,53

1500 0,31 0,041 4,27 13,37 31,96

Turbine 1

n

[rpm]

H

[mWc]

Torque [Nm]

Pm

[W]

Ph

[W]

η

[%]

750 2,1 1,69 132,51 183,16 72,34

1000 2 1,15 120,16 174,44 68,88

Turbine 2

n

[rpm]

H

[mWc]

Torque [Nm]

Pm

[W]

Ph

[W]

η

[%]

750 2 1,52 119,32 174,44 68,40

1000 1,8 1,00 104,67 157,00 66,67

Table 6 - Series-5BT Efficiency (Q=32 m3/h)

n

[rpm]

H

[mWc]

Torque

[Nm]

Pm

[W]

Ph

[W]

750 2,16 1,876 147,25 211,60

1000 2,10 1,277 133,66 206,17

1250 1,77 0,625 81,83 173,62

1500 1,72 0,354 55,65 168,19

Table 7 - Affinity Analysis: Case 1

10

Case 2: Diameter of 400 mm and flow rate of 74.54

m3/h

Table 8 - Affinity analysis: Case 2

7. CONCLUSION

In conclusion, since big hydro power plant are used from

many decades, they are currently deeply known and com-

monly used all over the world. Instead, the micro-hydro

converters are not well known yet. Anyway in the last

years, the research about this new configurations of tur-

bomachinery were developed. To improve and speed up

this process, the CFD modelling play an essential role.

Overall, nonetheless the simplification assumed since the

difficult of the real situation, the CFD simulations present

a valid option to extract a trustable results capable to pre-

view the fluid flow behaviour and to compare it with the

enables experimental data.

ABBREVIATIONS

3BT, Three blade turbine; 5BT, Five blade turbine; CFD, com-putational fluid dynamic; GHG, greenhouse gas; IEA, Interna-tional Energy Agency; NPSH, Net Positive Suction Head; PSH,

umped-storage hydropower; RES, renewable energy sources; TKE, Turbulent kinetic energy;

REFERENCES

Andersson B., Andersson R. (2012). Computational Fluid

Dynamics for Engineers, Cambridge University Press

Batchelor G.K. (2012). Introduction to fluid dynamics, Cam-

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Dixon S.L., Hall C. (6th ed. 2010). Fluid mechanics and ther-

modynamics of turbomachinery, Butterworth-Heinemann

Kudela H. (2010). Hydraulic losses in pipes, Journal of Sci-

ence, vol.1, Wrocław University of Technology

Ramos H. (2000). Guideline for design of small hydropower

plants, WREAN and DED, Belfast, North Ireland

Samora I., Franca M.J., Hasmatuchi V., Münch-Alligné C.,

Schleiss A.J., Ramos H.M. (2016), Experimental character-

ization of a five blade tubular propeller for inline installa-

tion, Elsevier Ltd.

n

[rpm]

H

[mWc]

Torque

[Nm]

Pm

[W]

Ph

[W]

750 8,64 15,00 1178,03 1692,79

1000 8,42 10,22 1069,29 1649,38

1250 7,09 5,01 654,67 1388,96

1500 6,87 2,83 445,17 1345,55