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DEVELOPMENT OF A VARIABLE SPEED PUMP USING
DOUBLY FED INDUCTION MACHINE
A PROJECT REPORT
submitted by
CB.EN.U4EEE10015 A.SURYA TEJA
CB.EN.U4EEE10017 B.VISHAL
CB.EN.U4EEE10035 L.NARAYANAREDDY
CB.EN.U4EEE10057 S.VAMSI KRISHNA
in partial fulfillment for the award of the degree
of
BACHELOR OF TECHNOLOGY
IN
ELECTRICAL AND ELECTRONICS ENGINEERING
AMRITA SCHOOL OF ENGINEERING, COIMBATORE
AMRITA VISHWA VIDYAPEETHAM
AMRITANAGAR, COIMBATORE- 641112
May 2014
AMRITA VISHWA VIDYAPEETHAM
AMRITA SCHOOL OF ENGINEERING, COIMBATORE, 641112
BONAFIDE CERTIFICATE
This is to certify that the project report entitled “Development of variable
speed pumped hydro system using doubly fed induction machine” submitted by
“A.SURYATEJA(EEE10015),B.VISHAL(EEE10017),L.NARAYANAREDDY(EEE10
035), S.VAMSIKRISHNA (EEE10057)” in partial fulfillment of the requirements for the
award of the Degree Bachelor of Technology in “ELECTRICAL AND ELECTRONICS
Engineering” is a bonafide record of the work carried out under my guidance and
supervision at Amrita School of Engineering, Coimbatore.
Mr. S. R.MOHANRAJAN Dr. K.C.SINDHU THAMPATTY
SUPERVISOR CHAIRPERSON
Assistant Professor (SG)
Department of Electrical and
Department of Electrical and Electronics Engineering,
Electronics Engineering, Amrita School of Engineering,
Amrita School of Engineering, Amrita Nagar, Coimbatore-641112
Amrita Nagar, Coimbatore-641112
This project report was evaluated by us on……….
INTERNAL EXAMINER EXTERNAL EXAMINER
ABSTRACT
Effective integration of energy generating mechanism with energy storage will help in
meeting the power demand at all times. Supply side management of power can be done
using pumped storage systems. The best machine suited for this system is DFIM. This
thesis is related to operating a DFIM in motoring mode to run a pump. The DFIM operates
in motoring mode during low loads so that excess power is given to the storage system.
Depending upon how much excess power is generated in the grid, the speed of the DFIM is
set and the load of the pump varies according to pump characteristics. In this thesis, the
DFIM was operated at all sub-synchronous speeds by using a fuzzy logic control
mechanism. The control mechanism involves giving accurate voltages, angles and slip
frequency to the rotor side of the machine to control the speed. Open loop test was done to
get the relationship between speed and rotor voltage as well as speed and rotor angle. This
was used in closed loop with a fuzzy logic controller.
CONTENTS
1 . INTRODUCTION ...............................................................................................10
1.1 OBJECTIVE.................................................................................................12
1.1.1 The objectives include:........................................................................12
2 LITERATURE SURVEY..........................................................................................13
3 . STUDY STATE ANALYSISANDDYNAMICMODELLING OF DOUBLY FED INDUCTION MACHINE:
16
3.1 STEADY STATE ANALYSIS OF DOUBLY FED INDUCTION MACHINE: .................19
3.2 DYNAMIC MODELLING of DOUBLY FED INDUCTION MACHINE:.....................21
3.2.1 Features of Dynamic Modeling: ...........................................................21
3.2.2 Dynamic Modeling based on Space Vector Theory:...............................21
4 . SIMULATION....................................................................................................24
4.1 SIMULATION BLOCK DIAGRAM ...................................................................25
4.2 Input blocks:..............................................................................................26
4.3 Output measurement:................................................................................27
4.4 DESIGN OF FUZZY LOGIC CONTROLLER: ......................................................29
4.4.1 CALUCLATINGVALUES OF VOLTAGEMAGNITUDE ANDANGLE TO BE GIVEN TO
ROTOR FOR DIFFERENT SPEEDS:.........................................................................29
4.5 BUILDING THE FUZZY INFERENCE SYSTEM: .................................................31
4.5.1 FIS Editor:...........................................................................................31
4.5.2 Membership Function Editor:..............................................................32
4.5.3 Rule Editor:........................................................................................35
4.6 SIMULATION RESULTS ...............................................................................36
4.7 INFERENCE:...............................................................................................42
5 . SOFTWARE DEVELOPMENT..............................................................................43
5.1 Introduction:..............................................................................................43
5.2 dsPIC30F4011 Digital Signal Microcontroller:...............................................44
5.3 Implementation of Control Algorithm:.........................................................44
5.4 Timer Circuit for ADC:.................................................................................44
5.5 Motor Control PWMmodule: .....................................................................45
5.6 ADC Module:.............................................................................................45
5.7 Implementation of Space Vector Algorithm:................................................46
5.8 Algorithm for SVPWM: ...............................................................................47
5.9 Flowchart:.................................................................................................48
5.10 Conclusion:................................................................................................49
6 . HARDWARE DESIGN.........................................................................................50
6.1 Introduction:.............................................................................................50
6.2 Current transducer:...................................................................................50
6.3 Voltage transducer:...................................................................................51
6.4 BI-QUAD FILTER.........................................................................................52
6.4.1 Application of bi-quad filter:...............................................................53
6.5 Precision rectifier:.....................................................................................53
6.6 Frequency to voltage converter: ................................................................54
6.7 Frequency multiplier: ................................................................................54
6.8 Analog to digital Conversion:.....................................................................55
6.9 Features of AD7607: ..................................................................................56
6.9.1 Applications of AD7607: .....................................................................56
6.9.2 Testing the ICAD7607: ........................................................................56
LIST OF FIGURES
Figure 3.1 Doubly Fed Induction Machine..................................................................16
Figure 3.2 Modes of operation of DFIM.....................................................................17
Figure 3.3 Steady State Equivalent Circuit of DFIM......................................................20
Figure 3.4 Dynamic Modeling equivalent circuit of DFIM.............................................22
Figure 4.1 Simulation of Block Diagram ......................................................................25
Figure 4.2 showing the speed input and torque being estimated for measuring the o/p mechanical
power.......................................................................................................................26
Figure 4.3 Asynchronous Machine given input from both stator and rotor ...................26
Figure 4.4 showing the output parameters being measured........................................27
Figure 4.5 Power output measurement block .............................................................28
Figure 4.6 Subsystem developedfor giving pulses to the rotor side inverter.................28
Figure 4.7 Speed(X) Vs Voltage (Y)..............................................................................30
Figure 4.8 Speed(X) Vs Angle(Y) .................................................................................31
Figure 4.9 Mamdani System ......................................................................................32
Figure 4.10 Load Torque...........................................................................................33
Figure 4.11 Voltage...................................................................................................34
Figure 4.12 Angle.....................................................................................................35
Figure 4.13 Rules ......................................................................................................36
Figure 4.14 Rotor input speed....................................................................................38
Figure 4.15 rotor output speed..................................................................................38
Figure 4.16 Rotor torque output................................................................................39
Figure 4.17 Stator active power,rotoractive powerandmechanical power(fromtoptobottom)
................................................................................................................................39
Figure 4.18 Stator active power................................................................................40
Figure 4.19 Rotor active power..................................................................................41
Figure 4.20 Output Mechanical Power .......................................................................41
Figure 5.1 a) 3-phased balanced voltages b) resulting space vector...............................47
Figure 5.2 Flow Chart of the Programme....................................................................49
Figure 6.1 shows the circuit of LA-25NP current transducer.........................................50
Figure 6.2 shows the circuit of potential transducer....................................................52
Figure 6.3 shows a typical three-operational amplifier circuit......................................53
Figure 6.4 precision rectifier......................................................................................54
Figure 6.5 Frequency to voltage converter..................................................................54
Figure 6.6 Frequency Multiplier.................................................................................55
LIST OF TABLES
Table 1 Speed voltage and Angle for fuzzylogic algorithm............................................29
Table 2 Closed Loop Simulation results.......................................................................36
LIST OF SYMBOLS
SYMBOLS DESCRIPTION UNIT
Rs Stator Resistance Ω
R Load Resistance Ω
X Load Reactance Ω
Xls Stator Leakage Reactance Ω
Xlr’ Rotor Leakage Reactance Ω
Rr’ Rotor Resistance Ω
Xm’ Magnetizing Reactance Ω
Ls Stator inductance H
Lr Rotor inductance H
Lm Mutual inductance H
E Air gap voltage V
s Slip
a Stator to rotor turns ratio
β Pitch angle Degre
e
ω Angular Frequency rad/s
Vdc DC link Voltage V
V Wind Speed m/s
ρ Air density kg/
v Volume of air
Cp Power coefficient
A Rotor swept area
Pt
λ
Turbine Power
Tip speed ratio
W
Vds d axis stator voltage V
Vqs
Vdr
Vqr
P
N
ids
iqs
idr
iqr
Te
Tm
q axis rotor voltage
d axis stator voltage
q axis rotor voltage
No of poles
Speed of rotor
Rotor electrical angular velocity
Rotor angular velocity
d axis stator current
q axis rotor current
d axis stator current
q axis rotor current
d axis stator flux
q axis stator flux
d axis rotor flux
q axis rotor flux
Stator real power
Stator reactive power
Rotor real power
Rotor reactive power
Stator current
Stator equivalent or rotor current
Stator Voltage
Electrical torque
Mechanical torque
V
V
V
rpm
rad/s
rad/s
A
A
A
A
web
web
web
web
W
W
W
W
A
A
V
Nm
Nm
1 . INTRODUCTION
The main essential characteristic of the grid is that the electric power
generated should be equal to the energy demand at any time. If they are not equal,
then there is a chance of loss of synchronization and it could lead to tripping of
load and in worst cases, tripping of the grid itself. So there is a need for a
sustainable technology that can meet the demand whenever needed. There is also
a need of effective integration of new energy generating mechanism, its energy
storage and transmission. All these together will improve not only the reliability
of grid but also the cost incurred in meeting them. A storage system helps in
improving the capability of system to provide energy when it is needed and store
the energy whenever it is produced in excess. There are many energy storage
technologies like Lead Acid Battery Storage and Lithium Ion Battery Storage,
Superconducting Magnetic Energy Storage, Fly Wheel Storage and Pumped
Hydro Systems (PHS). Among these the pumped hydro storage technology is
found to be more optimal when storage capacity and efficiency were compared
[1].
In future pumped hydro storage will stand alone as the most reliable
technology available for grid power storage. In the past decade, there has been a
tremendous increase in the wind and solar energy generation due to tax incentives
and other policies. So developing the Pumped Hydro Storage plants near the
places where there is a heavy chance of wind and solar energy generation can lead
to improved grid reliability and it will reduce the need of additional fossil-fuelled
generation.
The characteristics like grid reliability are considered because of the reason
that the wind blow is seasonal and solar energy is available only during daytime
[3]. There is more demand for the development of energy storage systems as
essential components for using renewable energy systems more efficiently and in
large amounts. The variable speed pumped storage technology provides fast
response in adjusting frequency regulation in both the generation and pumping.
PHS is the least expensive method of energy storage as it does not require any
additional fossil fuels for generating electricity. It is an emission free renewable
resource. It is the best storage alternative while meeting the demand for bulk loads
and is very quick in response. It is also having a high overall efficiency of about
70-80%. But these systems need lot of resources such as proper landscapes for
installing the systems [4]. The main limitation of the PHS system is that it needs
minimum one dam along the river streams or any water bodies that has a constant
flow of water resources. So initiatives should be taken to implement the projects
in sites where there will be minimal effects to the environment surrounding it. For
that a feasibility study has to be done in those areas where the plant
implementation is proposed. New approaches like locating reservoirs that are
physically separated from existing river systems must be encouraged. Efforts
should be taken to reduce the evaporation and seepage losses. There should be
regular treatment to the Pumped Hydro Systems for better performance. But these
systems will need less investment compared to flywheel, SMES, and battery
storage technologies [5], [6]. In these plants, the energy is stored in the form of
potential energy of water pumped up from a lower elevation reservoir to a higher
elevation [7]. During periods of high electrical demand, the stored water is
released through turbines to produce electric power by running an electrical
machine (like Synchronous or Induction) in generating mode and during the
process of pumping water from lower elevation to higher elevation, the electrical
machine is operated in motoring mode [8],[9]. The motoring mode and generating
mode can be achieved by either fixed or variable speed operations. The generating
set operates at constant speed and during this fixed speed operation, power input
is directly dependent upon the pumping head and cannot be adjusted. In variable
speed operation, pump mode enables operation with adjustable power input at
each of the required pumping head [10], [11], [12], thus providing regulated pump
operation.
Pump-turbine machines can be designed as fixed or variable speed machines.
Presently in our project we have simulated a variable speed machine system using
DFIM as machine. We only presented the motoring mode of the system i.e.,
connected to the pump.
1.1 OBJECTIVE
The project proposes a new control scheme for running DFIM in motoring
mode by connecting to a pump. The frequency and voltage for stator side are kept
constant. The rotor speed is adjusted and based on the speed the rotor voltage and
frequency is given to the rotor through fuzzy logic controller.
1.1.1 The objectives include:
 Developing a DFIM system running at variable speed connected to a
pump.
 Simulation of the DFIM system using Matlab/SIMULINK for
variable speeds by giving torque input using pump characteristics.
 Implementation of control logic using dsPIC30f4011.
2 LITERATURE SURVEY
[2.1] Andreas Oberhofer, “Energy Storage Technologies & Their Role in
Renewable Integration,” Global Energy Network Institute, July 2012.
“This paper presents an analysis on type of Energy Storage Techniques available
and their advantages and disadvantages. It describes the advantages of Pumped
Hydro Systems advantages over the other storage technologies. A critical
observation is made on the benefits, problems and possible impacts in the future.”
[2.2] Mahdi Johar, Ahmad Radan, Mohammad Reza Miveh and Sohrab
Mirsaeidi, “Comparison of DFIG and Synchronous Machine for Storage Hydro-
Power Generation”, International Journal of Pure and Applied Sciences and
Technology, 3-10-11.
“This paper deals with advantages and capabilities of variable speed storage –
pumping plants. These features were compared with conventional synchronous
ones in this paper. Different viewpoints such as structure and steady state
behaviour are focused for comparing the application of Doubly Fed
Induction Generators (DFIG) and synchronous ones in storage hydro plants.
Dynamic stimulations are also used to evaluate the performance of variable-
speed versus synchronous fixed-speed generation units.”
[2.3] Rajib Datta and V. T. Ranganathan, “Variable-Speed Wind Power
Generation Using Doubly Fed Wound Rotor Induction Machine-Comparison with
Alternative Schemes,” IEEE Transactions on Energy Conversion, Vol. 17, No. 3,
September 2002.
“ In this paper the DFIM is connected to grid and is controlled from rotor side.
The machine is compared in both fixed speed and variable speed systems using
cage rotor induction machine. The comparison is made using the major hardware
components required, energy output and operating region. This paper in detail
explains the advantages and flexibility of variable speed systems compared to
fixed speed systems. The DFIM is controlled from the rotor side in this paper. The
speed is controlled by varying the supply on the rotor side and connecting the
both rotor and stator to the grid. This paper shows that even though more
simple and reliable, Fixed Speed Systems have some limitations. The energy
capture can be increased significantly with connecting the DFIM for the variable
speed system.”
[2.4] P.Girihar Kini, “Effect of Voltage and Load Variations on Efficiencies of
a Motor-Pump System”,IEEE transactions on energy conversions,Vol.25,N0.2,
June 2010.
“This paper deals with a three phase induction motor connected to a centrifugal
pump model. In this model a DC motor is connected instead of pump to get the
Induction machine system characteristics. This model shows that a DC machine
can be used to replace the pump for determining the machine characteristics. The
motor pump system is subjected to voltage and load variations to justify the
system and for better result analysis.”
[2.5] Xibo Yuan and Jianyun Chai, “A Converter-Based Starting Method and
Speed Control of Doubly Fed Induction Machine with Centrifugal Loads”, IEEE
TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 47, NO. 3,
MAY/JUNE 2011.
“This paper deals with the speed control of DFIM connected with a converter on
the rotor side and rotor shaft connected to a centrifugal load. The paper
presents the converter based starting method for running the induction machine
with centrifugal loads. The machine is tested for variable speed operation. The
machine is again connected to the DC machine for analysis. This paper explains
the advantage of DFIM system connected to the pump.”
[2.6] Dorin O. Neacsu, “SPACE VECTOR MODULATION –An Introduction,”
The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001.
“This is a tutorial presented by the author on the basics of Space Vector Pulse
Width Modulation. The basics on Vectoral Analysis of Three Phase Converter,
Pulse Width Modulation and Selection of the switching sequence were explained
in detail. The Comparison is made on the different methods of generating
SVPWM and the THD, Number of Switching States and dominant harmonics
were analysed.”
[2.7] Subrata.K.Mondal and Bimal.K.Bose, “Space Vector Pulse Width
Modulation of Three-Level Inverter Extending Operation Into Overmodulation
Region,” IEEE transactions on Power Electronics, Vol.18, No.2, March 2003.
This Paper deals with the Space Vector Pulse Width Technique and it’s over
modulation and under modulation methods. The paper deals with Space Vector
PWM and its control algorithm for DSP based implementation. The voltage and
angle were given as inputs to the algorithm and it creates SVPWM pulses using it
at 1.0 kHz switching frequency. In this method the switching states are distributed
such that the neutral point voltage always remains balanced. An open loop V/f
controlled induction motor drive has been evaluated using both over modulated
and under modulated strategies by giving the voltage and frequency in whole
speed range.”
3 . STUDY STATE ANALYSIS AND DYNAMIC
MODELLING OF DOUBLY FED INDUCTION
MACHINE:
Figure 3.1 Doubly Fed Induction Machine
DFIM is a Wound Rotor Induction Machine with AC supply given to both
stator and rotor. The PWM back to back inverter is connected to the rotor side.
The main advantage of this system is the capability of rotor circuit in allowing the
bidirectional flow of power in both sub-synchronous mode and super-synchronous
mode [21]. The power rating of the converter is also reduced as it is connected to
the rotor side. It is to note that the number of turns in stator should be more than
the number of turns in the rotor [24]. With the voltage reduction in the rotor side,
it is possible to operate at a lower DC bus voltage. Consequently the voltage
ratings for the devices and the capacitor bank can be optimized [25]. So, for the
same power rating, the power generated by this system is higher compared to
other systems. Its speed range is very high. It can run both in sub synchronous
mode and super synchronous mode based on the requirement [26], [27].
Figure 3.2 Modes of operation of DFIM
Variable speed operation is having more advantages than fixed speed for
large scale turbine. The main advantage of the DFIM is that the power processed
by the power converter is only the slip power, it is only a fraction of total power.
If it is operated within a speed range preferably around the synchronous speed,
then the power converter rating can be reduced drastically. This is more
advantageous for centrifugal loads as pumps. The speed limit is set by the rating
of the converter we deploy in the system. If it goes beyond this speed then the
converter loses control. So it will have a little problem in starting. To solve this
problem, starting resistors or autotransformers can be used. It is applicable to PHS
as the system is having apparatus of high capacity. In a grid controlled DFIM
system, the voltage and frequency are imposed by the grid. So, the active power
and reactive power control should be taken care of. If it is made to run as stand-
alone, voltage and frequency should also be regulated. The active and reactive
power flow control is the main concept behind the control methods. The active
and reactive power oscillations of DFIM under voltage sag are very less and are
only for fraction of seconds. If the reference reactive power is set then the reactive
power suddenly increases and then reduces to the rated value. Even the DC link
voltage will oscillate for some time and settles quickly. When the grid voltage
reduces, the rotor flux also gets reduced. Under voltage swell i.e., when voltage is
increased to more than rated value the active power again oscillates and settles at
rated value. The reactive power suddenly reduces and comes to the rated value.
Compared to the Synchronous machine and Induction machine drives, DFIM
has better efficiency. It does not require high rating power converters as they can
be connected to the rotor side with half the power rating [30], [31]. They have
better dynamic stability than the other machines under variable speed operation.
The time taken for them to convert from motor to generator is less compared to
other machines. The amount of power generated using the same size machine for
DFIM will be more compared to other machines [32]. During motor condition in
sub-synchronous mode, the rotor generates power and in super synchronous
mode, it absorbs power. In generator condition the rotor absorbs power at sub
synchronous mode and produces power in super synchronous mode.
When comparing the dynamic behavior the factors voltage drop test, testing
for torque perturbations, behavior of the systems based on inter area oscillations
are considered[33]. When compared the synchronous machine has less voltage
drop and the variable speed machine DFIM has high voltage drop but the time
taken to stabilize the active power and reactive power is less. In case of torque
disturbances the variable speed has more advantage than the fixed speed as the
change in torque is stabilized by the change in the speed which has to compensate
by power flow control in synchronous machine [34]. In a variable speed system
the torque disturbances will never be a problem. The synchronous machine
provides good damping for active power oscillations only until certain frequency
while the variable speed machine provides good damping for a better frequency
range. With or without Power System Stabilizer, the behavior of reactive power
and stator voltage are similar. If we consider reactive power, the behavior of
synchronous and variable speed machines fluctuates for different frequency
ranges. For one frequency range, one machine behaves better than the other. For a
lower frequency range, the variable speed machine has better behavior because it
has constant amplitude. For a higher frequency range, the synchronous machine
has better behavior. Compared to DFIG with same speed and power, a
synchronous machine has smaller dimensions and inertia with a larger air gap.
With lesser rotor current, DFIG can generate same active and reactive power as a
synchronous machine. So, synchronous machine is not as cost effective as DFIG.
3.1 STEADY STATE ANALYSIS OF DOUBLY FED
INDUCTION MACHINE:
The steady state analysis of DFIM consists of equivalent circuit of it. In this
circuit
 It is assumed that both the stator and the rotor are connected in the
star configuration; however, only one phase of the stator and rotor three-
phase windings is represented.
 The stator is supplied by the grid at constant and balanced three-
phase AC voltage amplitude and frequency.
 The rotor is supplied also at constant and balanced AC voltage
amplitude and frequency, independently from the stator, for instance, by a
back-to-back voltage source converter.
 To represent steady state voltage and current magnitudes, the
analysis is carried out using classical phasor theory: [1]_DFIG
Vs = supply stator voltage
Vr = supply rotor voltage
Is = induced Stator Current
Ir = induced rotor current
Es = induced EMF in the stator
Ers= induced emf in the rotor
 The equivalent circuit of DFIM is
Figure 3.3 Steady State Equivalent Circuit of DFIM
So when representing the equivalent circuit the equation w.r.t is given by
𝑉𝑟
𝑠
− 𝐸𝑠 = (
𝑅 𝑟
𝑠
+ 𝑗𝑤𝑠𝐿 𝑟)𝐼𝑟 𝑎𝑡 𝑓𝑠
By this equation we can understand that the injected voltage on the rotor side
can be determined if the rotor current and stator voltage are known at a particular
slip.
The rotor voltage is given by
𝑉2𝑝 ′ = 𝐸 + 𝐼2𝑝 ′ (
𝑅2
𝑠
+ 𝑗𝑋2)
𝓋2𝑝 = 𝑉2𝑝
′
(
𝑠
𝑎
) 𝑤. 𝑟. 𝑡 𝑠𝑡𝑎𝑡𝑜𝑟
The rotor current and frequency are given by
𝐼2𝑝 = 𝑎𝐼2𝑝′
𝑓𝑟 = 𝑓𝑠 − (
𝑃𝑁
120
)
The real power and reactive power supplied to the load were given by
𝑝1 = 3𝑅𝑒(𝑉1𝑝 𝐼1𝑝
∗
)
𝑞1 = 3𝐼𝑚(𝑉1𝑝 𝐼1𝑝
∗
)
The real power and reactive power supplied to the load from rotor were given
by
𝑝2 = ±3𝑅𝑒(𝑉2𝑝 𝐼2𝑝
∗
)
𝑞2 = 3𝐼𝑚(𝑉2𝑝 𝐼2𝑝
∗
)
The output mechanical power is given by
𝑝 𝑚 = 3𝐼2𝑝
2
𝑅2 (
1 − 𝑠
𝑠
) − 𝑝2 (
1 − 𝑠
𝑠
)
3.2 DYNAMIC MODELLING of DOUBLY FED INDUCTION
MACHINE:
3.2.1 Features of Dynamic Modeling:
 Dynamic Modeling explains and defines the behavior of the machine’s
variables in transition periods as well as in the steady state.
 By means of the dynamic model it is possible to know at all times the
continuous performance of the variables of the machine, such as torque,
currents, and fluxes.
 In this way, by using the information provided by the dynamic model, it is
possible to know how the transition from one state to another is going to
be achieved, allowing one to detect unsafe behaviors, such as instabilities
or high transient currents.
 The dynamic model also provides additional information of the system
during the steady state operation, such as dynamic oscillations, torque or
current ripples.
3.2.2 Dynamic Modeling based on Space Vector Theory:
It is represented in general in differential equation form, is often structured as a
compact set of model equations.
 The DFIM equivalent electric circuit is shown below,

Figure 3.4 Dynamic Modeling equivalent circuit of DFIM
 The instantaneous stator voltages, current and fluxes of the machine can be
described by the following electric equations
𝑣 𝑎𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑎𝑠( 𝑡) +
𝑑𝜓𝑎𝑠 (𝑡)
𝑑𝑡
𝑣 𝑏𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑏𝑠( 𝑡) +
𝑑𝜓 𝑏𝑠(𝑡)
𝑑𝑡
𝑣𝑐𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑐𝑠( 𝑡)+
𝑑𝜓𝑐𝑠 (𝑡)
𝑑𝑡
Rs is the stator resistance; ias(t), ibs(t) and ics(t) are the stator currents of
phases a, b, and c; vas(t), vbs(t), and vcs(t) are the applied stator voltages;
and cas(t), cbs(t), and ccs(t) are the stator fluxes
 The rotor magnitudes are described by the following equations. Here, Rr is
the rotor resistance referred to the stator; iar(t), ibr(t), and icr(t) are the
stator referred rotor currents of phases a, b and c; var(t), vbr(t) and vcr(t)
are the stator referred rotor voltages; and car(t), cbr(t) and ccr(t) are the
rotor fluxes.
𝑣 𝑎𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑎𝑟( 𝑡) +
𝑑𝜓𝑎𝑟 (𝑡)
𝑑𝑡
𝑣 𝑏𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑏𝑟( 𝑡) +
𝑑𝜓 𝑏𝑟 (𝑡)
𝑑𝑡
𝑣𝑐𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑐𝑟( 𝑡) +
𝑑𝜓𝑐𝑟(𝑡)
𝑑𝑡
 Alpha-beta Model: the voltage equations of the DFIM in space vector
form:
𝑣⃗ 𝑠
𝑠
= 𝑅 𝑠 𝑖⃗𝑠
𝑠
+
𝑑𝜓⃗⃗ 𝑠
𝑠
𝑑𝑡
𝑣⃗ 𝑟
𝑟
= 𝑅 𝑟 𝑖⃗𝑟
𝑟
+
𝑑𝜓⃗⃗𝑟
𝑟
𝑑𝑡
 superscripts “s” and “r” indicate that space vectors are referred to stator
and rotor reference frames, respectively and the correlation between the
fluxes and the currents, in space vector notation, is given by the following
equation where Ls and Lr are the stator and rotor inductances, Lm is the
magnetizing inductance
𝜓⃗⃗𝑠
𝑠
= 𝐿 𝑠 𝑖⃗𝑠
𝑠
+ 𝐿 𝑚 𝑖⃗𝑟
𝑠
𝜓⃗⃗ 𝑟
𝑟
= 𝐿 𝑚 𝑖⃗𝑠
𝑟
+ 𝐿 𝑟 𝑖⃗𝑟
𝑟
For transforming all equations into stator reference frame we use the
equation
Now the equations become:
𝑣⃗ 𝑠
𝑠
= 𝑅 𝑠 𝑖⃗𝑠
𝑠
+
𝑑𝜓⃗⃗ 𝑠
𝑠
𝑑𝑡
𝑣⃗ 𝑟
𝑠
= 𝑅 𝑟 𝑖⃗𝑟
𝑠
+
𝑑𝜓⃗⃗𝑟
𝑠
𝑑𝑡
− 𝑗𝜔 𝑚 𝜓⃗⃗𝑟
𝑠
𝜓⃗⃗𝑠
𝑠
= 𝐿 𝑠 𝑖⃗𝑠
𝑠
+ 𝐿 𝑚 𝑖⃗𝑟
𝑠
𝜓⃗⃗𝑟
𝑠
= 𝐿 𝑚 𝑖⃗𝑠
𝑠
+ 𝐿 𝑟 𝑖⃗𝑟
𝑠
4 . SIMULATION
The Simulation of the DFIM is made using the MATLAB/SIMULINK.
The machine speed and torque are given as input. The speed and torque are related
by the pump characteristics as torque is proportional to square of speed. Torque is
given positive and the machine runs as motor. The main objective is to obtain
different speeds for different torque values and optimize the power taken out from
the grid. So the speed reference is given to the machine based on the power
available on the grid. So the frequency of grid helps in giving this parameter.
The parameters that required for simulation are measured by doing no load
test and block rotor test on the machine. The parameters are found to be
 Power Output (VA): 1100VA
 Voltage Line to Line: 415 V
 Frequency: 50Hz
 R stator =6.4Ω ; L stator= 0.183H
 R rotor =9.8903Ω ; L rotor =0.0224H
 L mutual = 0.208H Pole pairs = 3.
The figure shown below is the Simulink model of the simulation. It consists of a
three phase asynchronous induction machine connected to the inverter. The
voltage is injected on the rotor side by giving the Space Vector Pulse Width
Modulation (SVPWM) pulses. The machine parameters are fed to the
asynchronous machine model and a fuzzy control method is used to control the
machine speed for different voltage and slip frequencies injected to the rotor.
The speed parameter is given as input to the machine and voltage and
angle to be injected to the rotor are obtained by fuzzy logic control. Then these
parameters are fed to the SVPWM generator. The generated pulses are fed to
inverter as pulses and the desired voltage and slip frequency values are produced.
The torque and power are measured by power measuring blocks. The total
mechanical power should be equal to sum of rotor and stator input power which is
observed in simulation. This method will provide a new method of controlling
speed with optimizing power loss.
4.1 SIMULATION BLOCK DIAGRAM
Figure 4.1 Simulation of Block Diagram
4.2 Input blocks:
Figure 4.2 showing the speed input and torque being estimated for measuring the o/p
mechanical power.
The speed is first converted to rad/sec to the rotor side of the machine and the
torque input is estimated from the sped input and is given by the equation
T= (0.957870572e-3)*N2.
Where N is speed and T is Torque.
Figure 4.3 Asynchronous Machine given input from both stator and rotor
The stator side is supplied from the three phase AC source and the rotor side is
supplied from the inverter. The inverter is fed from a DC source. When the
machine runs in sub-synchronous motor operation then the rotor will give out the
power which is proportional to the slip of the machine. And the rotor supply is at
slip frequency. The DC voltage given in the system is 80V (but given the turns
ratio the voltage is given as 715 volts). The supply given to the rotor side from the
inverter is given with slip frequency fs. Where fs=(f-fr). Where fr is frequency of
rotation of rotor.
4.3 Output measurement:
Figure 4.4 showing the output parameters being measured
The parameters needed to be measured are selected from bus selector that is given
to the measurement pin of machine. The rotor currents, Electromagnetic torque,
Speed and Rotor angle are measured from it.
Figure 4.5 Power output measurement block
For measuring the instantaneous active and reactive power . The blocks will give
the mean value of power when the 3-phase voltage and power are given to it.
The rotor and stator real and reactive power are measured by the blocks as shown
in Fig.6. The blocks will give the mean value of power when the 3-phase voltage
and power are given to it.
Figure 4.6 Subsystem developed for giving pulses to the rotor side inverter
After measuring the rotor voltage angle and slip frequency through the control
loop the parameters are given to a VVVF source and the voltage, instantaneous
angle is measured with PLL and given to the ABC to DQ conversion block and
from there to Alpha-Beta then to pulses generator. Thus the pulses are generated
and given to the inverter on the rotor side.
4.4 Design of Fuzzy Logic Controller:
To control the Doubly Fed Induction Machine by using a set of predefined rules
obtained from open-loop test, a fuzzy inference system can be used. Fuzzy
inference process helps in formulating the mapping from a given input to an
output using fuzzy logic. Here, Mamdani-type fuzzy inference system is used.
4.4.1 Calculating Values of Voltage Magnitude and Angle to be Given to Rotor
For Different Speeds:
For designing the fuzzy logic controller, we need to know the values of inputs and
outputs to be given and taken from the fuzzy inference system.
Here the input is speed reference and outputs are voltage magnitude and voltage
angle which are to be given to the rotor. The magnitude and angles are given to
the rotor along with slip frequency. Speed of the rotor depends to a large extent on
the slip frequency given to the rotor.
Through trial and error, the values of voltage and angle were found for
approximately 20 different slip values using open loop test.
Table 1 Speed voltage and Angle for fuzzylogic algorithm
SPEED
(rpm)
VOLTAGE MAGNITUDE(V) VOLTAGE ANGLE
900 20 20
850 40 40
800 46 45
750 60 61
700 110 80
650 113 85
600 125 100
550 155 110
500 170 115
450 180 117
400 190 119
350 200 119
300 215 119
200 246 119
The relation between speed and voltage is found to be linear.
Figure 4.7 Speed(X) Vs Voltage (Y)
The relation between speed and angle is linear for higher values of speed. For
lower values of speed, the angle required to be given is almost constant.
Figure 4.8 Speed(X) Vs Angle(Y)
Now that the inputs and outputs are found out, the fuzzy inference system can be
designed which can take any value between 0 and 1000 as speed reference input
and it can generate corresponding voltages and angles.
4.5 BUILDING THE FUZZY INFERENCE SYSTEM:
The graphical tools which were used to build and edit fuzzy inference system are:
1. Fuzzy Inference System (FIS) Editor
2. Membership Function Editor
3. Rule Editor
4.5.1 FIS Editor:
This editor displays information about fuzzy inference system. Here, we use a 1
input and 2 output system. The input is load in terms of speed and outputs are
voltage magnitude and voltage angle to be given to sub-system which generates
reference signals for inverter.
Figure 4.9 Mamdani System
4.5.2 Membership Function Editor:
The membership functions associated with all input and output variables of the
fuzzy system can be edited here. The membership function type chosen for load
torque is trapezoidal type. For voltage and angle the membership function type
chosen is Gaussian. Here, the load torque being in terms of speed is split into 16
membership functions with a range from 0 to 1000. The voltage is in the range of
0 to 300 while the angle is in the range of 0 to 120.
Any changes in membership functions are reflected in the rules. Based on the
values obtained in the open loop test, the membership functions are edited so that
every input from 0 to 1000 can be mapped to a certain voltage output and angle
output by using if-then rules.
The membership functions for load torque, voltage and angle are shown below.
Figure 4.10 Load Torque
For example, let us consider the membership function with the name as 850. This
membership function takes all values between 825 and 875. Similarly,
membership function with name 500 takes all values from 475 to 525. The
membership functions used here are trapezoidal membership functions. The
membership functions are made to overlap each other. This is because, if
overlapping is not done, the border values give wrong results when used in
simulation.
Figure 4.11 Voltage
For voltage and angle, the membership functions used here are gaussian
membership functions. The angle varies from 20 degrees to 119 degrees
proportionally with slip and voltage increases from 20V to 277V for slip varying
from 0.1 to 0.9.
Also the magnitude of voltage generated is same for all values in a
particular membership function. Similarly the magnitude of angle generated is
also same for a particular membership function. So make the behavior linear, we
need to use more membership functions. This helps in making the result piecewise
linear.
Figure 4.12 Angle
4.5.3 Rule Editor:
Based on the open-loop test values, all the inputs can be mapped to corresponding
outputs by using the if-then rules. The rule editor is shown below. Each
membership function is labelled by its peak value. This makes the rule editing
easier.
Figure 4.13 Rules
Now, the fuzzy inference system is designed. It is then exported to Matlab
workspace and used in Simulink.
4.6 SIMULATION RESULTS
The simulationistestedbyusingastep-loadinput varying from 0 to 10 N-m. The load is
given in terms of speed. For this variable load, the rotor speed, stator power, rotor
power, mechanical power and rotor torque are plotted.
The results are shown below.
Table 2 Closed Loop Simulation results
SPEED
(rpm)
VOLTAGE
MAGNITUDE(V)
VOLTAGE
ANGLE
STATOR
ACTIVE
POWER(W)
ROTOR ACTIVE POWER(W)
900 20 20 110 -90
850 40 40 960 -53
800 46 45 920 -97
750 60 61 855 -112
700 110 80 630 -142.5
650 113 85 560 -210
600 125 100 500 -230
550 155 110 400 -290
500 170 115 350 -310
450 180 117 305 -290
400 190 119 290 -260
350 200 119 280 -195
300 215 119 250 -175
200 246 119 200 -147
Figure 4.14 Rotor input speed
Figure 4.15 rotor output speed
Figure 4.16 Rotor torque output
Figure 4.17 Stator active power, rotor active power and mechanical power (from top to bottom)
Figure 4.18 Stator active power
Figure 4.19 Rotor active power
Figure 4.20 Output Mechanical Power
4.7 INFERENCE:
1. Rotor speed increases proportionally with the increase in load. As the slip
frequency varies, rotor speed varies according to the value of slip
frequency given to the rotor.
2. Stator active power and mechanical power also increase with the increase
in load.
3. Rotor power, being directly proportionally to slip and stator active power
will decrease in magnitude as the load increases. This is because as load
increases, slip decreases.
4. But for lower values of load, the rotor power behaves differently because
the value of stator active power is very low.
5. Rotor torque increases proportionally with increase in load.
6. For operating Doubly Fed Induction Machine with a pump, the machine
must run at a speed proportional to the load on the pump because torque of
the pump is directly proportional to the square of the speed. Here the speed
control is done according to pump characteristics.
7. For higher load torque on the pump, we run the DFIM at higher speed and
vice versa.
5 . SOFTWARE DEVELOPMENT
5.1 Introduction:
The coding for the digital signal processor is done in MPLAB IDE v8.46 from
Microchip Technology Inc. The programming was done in C platform. For this
MPLAB has a language tool suite add-on called MPLAB C30 compiler. The
complete standard C library is provided with the MPLAB C compiler for dsPIC
DSCs. MPLAB allows the user to view certain waveforms in its logic
analyser like PWM, port outputs etc. Also different types of inputs can be
given to the simulator using stimulus by register injection, clock stimulus,
asynchronous stimulus etc. The register values can be viewed through watch
window. The code is converted to hex file format after compiling and the
dsPIC30F4011 DSC is programmed using LabProg IC programmer.
For implementing control algorithm of DFIG the timer modules, ADC module
and PWM modules are used. In order to implement the control algorithm for
DFIG the code for the project is divided into different modules. The ADC
module and PWM modules were tested independently using the clock
stimulus and the logic analyser which is available in the MPLAB. Finally
the complete program for implementing the control algorithm is done by
clubbing all the individual programs.
The different sections of the program are as follows:
 A frequency control algorithm for determining the output frequency
of the PWM.
 A voltage control algorithm for fixing the output voltage magnitude
 PWM module for generating the SVPWM pulses
 Fuzzy logic programme for generating voltage and angle with a particular
speed
 Different timer modules for co-ordinating different peripherals.
5.2 dsPIC30F4011Digital Signal Microcontroller:
It is a 16 bit high performance digital signal controller which uses
Modified Harvard Architecture. The C Compiler optimized instruction set
architecture with flexible addressing modes. It is having 83 Base Instructions.
Each instruction is 24-bit wide, 16-bit wide data path. The main speciality of
dsPIC30f4011 is 24 Kbytes On-Chip Flash Program Space (8K instruction words)
which is very efficient in storing the look up tables. it is possible to use DC to 40
MHz external clock input. But in our purpose we are using 20MHz crystal
oscillator to give external clock input. So each instruction will take .2
micro seconds execution time. There are 12 peripherals and 29 interrupt
sources are available in the controller. We can assign priority to different
interrupt sources. Among these peripherals the peripherals used for
implementing the control algorithm for DFIG includes the following.
 I/O Ports
 Timers
 10-bit A/D Converter
 Motor control PWM module
 UART Module
5.3 Implementation of Control Algorithm:
 Initially the value of speed is given by a anolog pin to channel CH0 from
AN1.
 Then with fuzzylogic the voltage and angle for that particular speed is
estimated.
 This voltage and angle value will be fed to SVPWM control algorithm
made in the programme to provide six inverter pulses.
5.4 Timer Circuit for ADC:
The device has got 5 16bit timers, which can be operated either in timer mode or
in counter mode. The one of the important feature of these timers are that it can be
operated in pairs, so that we will get 32bit count. In this work two timers are used
here.Timer1 is used to update the PDC and Timer3 to update the value to the
ADC.Timer1 is configured to operate for 0.3ms to update the PDC register
Timer2 is configured to operate for .8ms to trigger the ADC module. The
flow chart for ADC sampling process is given in the figure. The TxCON and PRx
are the registers which need to be configured while doing programming
with the timers.
5.5 Motor Control PWM module:
The dsPIC30F4011 has a dedicated peripheral module for generating PWM
pulses, called the MCPWM module. The device has got 3 PWM modules with 2
PWM pins per module. The PWM pins can be configured to work in
independent mode or in complimentary mode. In this work it is configured
to operate in complimentary mode. A programmable dead time generator is also
present to introduce sufficient dead time when working in complimentary mode.
In this work a dead time of 3μsec is used. The MCPWM module can be operated
in different modes like free-running mode, edge triggered mode, centre
aligned mode, up-down counting mode etc. In this work up-down counting
mode is chosen. The switching frequency of SPWM is 2.5 kHz. The PWM
module is configured to operate at this frequency. The count to be loaded for this
in PTPER register is calculated as follows
5.6 ADC Module:
The10-bit high-speed analog-to-digital converter (A/D) allows conversion of an
analog input signal to a 10-bit digital number. This module is based on a
successive approximation register (SAR) architecture, and provides a
maximum sampling rate of 500 ksps. The A/D module has 16 analog inputs
which are multiplexed into four sample and hold amplifiers. The output of the
sample and hold is the input into the converter, which generates the result. The
A/D module is having six 16 bit configuration registers which includes
ADCON1, DCON2,ADCON3, ADPCFG, ADCHS, ADCSSL.
For the closed loop control algorithm for the DFIG, both the speed as well
as the stator voltage references is giving to the ADC pins in terms of
analog values. AN0 pin holds the speed reference and AN1 pin holds the stator
voltage reference. A sampling time of .8mSec is used for sampling.
Simultaneous sampling is enabled by configuring the ADCON1 register, so
that timing complications will be eliminated. The conversion and sampling is
configured to automatic mode. That is internal counter ends sampling and the next
sampling starts immediately after previous conversion. Interrupts are generated
after every 2nd sample/covert sequence. A/D conversion clock is set to 2Tcy =
0.1μs. The sampled values will be stored in ADCBUF0&ADCBUF1 registers.
The result of the ADC is a 10 bit digital value. Since the reference voltage to the
ADC is 5V, therefore when a 5V analog signal is detected then the result stored in
the ADC buffer will be 1023 (2^10 – 1). Hence when x voltage is detected, then
the value of x can be obtained as, x*(1000/1023). Here the value needed is from 0
to 1000 as this value is given for varying speed.
5.7 Implementation of SpaceVector Algorithm:
Space vector pulse width modulation technique was used for the switching of
SEMIKRON inverter in this project due to the following merits.
 High DC link voltage utilisation.
 Very much suited for digital implementation
 Reduced harmonics and losses.
The space vector modulation technique is somewhat similar to the
Sine+3rd harmonic PWM technique but the method of implementation is different.
Similar to the rotating magnetic field in the case of 3 phase machines, that is
if a three phase balanced voltage is applied to the windings of a three-phase
machine, a rotating voltage space vector may be talked of. The resultant voltage
space-vector will be rotating uniformly at the synchronous speed and will
have a magnitude equal to 1.5 times the peak magnitude of the phase voltage.
Each vector corresponds to a switching state, at that state we will obtain
the corresponding voltage magnitude at the 3phase output as mentioned in the fig
5.5(a). The intermediate magnitudes will obtained by the combination of the
fundamental switching states. The fundamental frequency can be adjusted
by adjusting the angular velocity of the vector. The phase sequence of the
output voltage can be controlled by changing the direction of rotation of the
vector. Both are very important as far as this project is concern.
Figure 5.1 a) 3-phased balanced voltages b) resulting space vector
5.8 Algorithm for SVPWM:
1. First find out the input dc link voltage (Edc), desired output frequency
‘f OP’ desired phase sequence of output voltage, desired magnitude of output
voltage and the desired switching frequency. During each sampling time
period three switching take place, where one turn-on and one turn-off
is taken as one switching.
2. Calculate magnitude factor ‘α’ from the knowledge of input dc link voltage
and the desired output voltage.
α Edc= 3/2 times peak of phase voltage. (5.4.a)
3. Also calculate the sampling time period
TS= 1/(3 fSW) (5.4.b)
4. Initialize sector position = I, and angle ‘θ’ = 0. Assume the rotating space
voltage vector to remain stalled at this position for the sampling time
period ‘TS’. Calculate the time duration for active and null state vectors by
the equations.
5. Output the inverter switching pulses as per the calculated time durations so
as to realize the space vectors in the following sequence: V (111), V1(101),
V2(100), V7(000).
6. Calculate the next position angle = + 2 for clockwise rotation, and = − 2 for
anti-clockwise rotation. Recalculate the time durations as in step (3) above
but this time the switching sequence will be V7(000), V2(100), V1(101),
V8(111).
7. Step (4) is to be repeated but every time the switching sequence alternates
between the sequences given in steps 4 and 5. When the space vector enters
sector-II (θ ≥ π/3), the vector is replace by V2 and V2 is replaced by V3. The
process continues to produce a continuously rotating voltage space vector
of fixed magnitude and fixed speed
5.9 Flowchart:
The flow chart algorithm is presented below
Figure 5.2 Flow Chart of the Programme
5.10 Conclusion:
Coding of the controller was performed in MPLAB. The output pulses were
observed in logic analyser. Both the fundamental voltage and frequency are
varying precisely with the references given in the ADC pin of the dsPIC.
6 . HARDWARE DESIGN
6.1 Introduction:
This part of the project work describes hardware control circuit design both for
controlling the stator voltage and frequency of the DFIG. potential transducer is
designed for 500V line voltage and a current transducer of 25A is designed in
order to obtain the rotor current and the values obtained after the design are
standardized.
6.2 Current transducer:
Current transducer is generally used for the electronic measurements of currents:
DC, AC, pulsed mixed with a galvanic isolation between the primary circuit and
the secondary circuit. Current transducer is preferred usually due to its added
features and advantages like accuracy, linearity, low temperature drift, optimized
response time, wide frequency band width, no insertion losses, high immunity to
external interference and also due to its current over load capability. So for the
above features and advantages the current transducer that best suites is LA 25-NP
for which the primary current nominal is in the range of (5-25) A. Based on the
data sheet of LA 25-NP design is done and explained below.
Figure: 1.1
Figure 6.1 shows the circuit of LA-25NP current transducer
The relation between the turn’s ratio and the currents is given below
𝐓. 𝐑 = 𝐧 =
𝐍𝐩
𝐍𝐬
=
𝐈𝐬
𝐈𝐩
Is = Ip (
Np
Ns
)
Where the turn’s ratio is decided based on the recommended connections stated in
the data sheet.
From the above diagram primary current (IP) *(1/1000) = IS
25*1.414*(1/1000) = IS =0.0353A
2.5v = IS*RM
RM = 2.5/0.0353= 70.82 ohms
6.3 Voltage transducer:
The pic cannot withstand DFIG stator voltage directly. The input that is given to
the pic should be in the range of (0-5) v. So the stator voltage of DFIG has to be
scaled down to 5v. For that we need the potential transformer. In this project, we
need to convert a 500V to a 2.5V. So we selected the potential transformer LV-
20P. As per the data sheet of the potential transformer the primary current of the
PT should not exceed 10mA. So it is essential to introduce a power resistor in the
primary circuit to limit the primary current. The design procedure of the potential
transformer is given below. The PT is designed for maximum of 500V input
voltage Maximum allowable primary current in PT=10mA. So the value of the
resistor that has to be added to the primary circuit is known from the current and
the voltage values stated above
Input resistance to the PT = 94kΩ (standardized value)
Input current =500/94k= 5.319mA
PT turns ratio (n) =2500:1000
Secondary current =5.319mA*2.5=13.297mA=0.01329A
Secondary rms voltage=2.5/1.414=1.7677V
Measuring resistance needed= 133.0Ω
The connection diagram of the PT is shown below and the measuring
Resistance is selected in such a way that the maximum potential drop across the
secondary should be 2.5V
Figure: 1.2
Figure 6.2 shows the circuit of potential transducer
6.4 BI-QUAD FILTER
The bi-quad configuration is a useful circuit for producing band pass and low-pass
responses, whereas the bi-quad and the state variable filter circuit configuration
can have Q-factor values of 400 or greater and at high frequencies operation of bi-
quad filter gives an efficient way of filtering the responses of the various inputs
given. So in this project bi-quad filter is used to filter the voltage response taken
from the speed of the rotor.
Figure: 2.1
Figure 6.3 shows a typical three-operational amplifier circuit
6.4.1 Application of bi-quad filter:
1) It is easily tunable using single resistor tuning (normally a stereo or ganged
potentiometer).
2) It can be configured to produce a Butterworth or a Chebychev response by
changing the damping (1/Q)
6.5 Precisionrectifier:
A simple rectifier circuit uses a diode and there is a turn on voltage for the diode.
The input voltage has to exceed the turn on voltage (0.6v for ordinary si diode)
before rectification is achieved. A precision rectifier is an active circuit using an
op amp and a diode in the feedback loop. This over comes the turn on Knee
voltage. The op amp reduces the turn –on voltage of a diode in its feedback loop
by a factor equal to the open loop gain of the op amp. For practical op amp gains
this reduces the forward voltage to a fraction of mv. Thus giving a precision
rectifier or near ideal diode characteristic for the rectifier function. This is how a
precision rectifier circuit differs from the simple rectifier circuit. In this project the
voltage pulses taken from the bi-quad filter is rectified by using precision rectifier
circuit.
Figure 2.2
Figure 6.4 precision rectifier
6.6 Frequency to voltage converter:
The rectified input from the precision rectifier is given to the frequency to voltage
converter. Now the voltage-to-frequency converter provides an output frequency
accurately proportional to its input voltage.
Figure2.3
Figure 6.5 Frequency to voltage converter
6.7 Frequency multiplier:
A frequency multiplier has the property that the frequency of the output signal has
an integer multiple of the input frequency. Based on this property the frequency
input from the converter circuit is given to the frequency multiplier to get desired
frequency.
Figure 2.4
Figure 6.6 Frequency Multiplier
6.8 Analog to digital Conversion:
The AD76071 is a 14-bit, simultaneous sampling, analog-
to- digital data acquisition system (DAS). The part contains analog input clamp
protection; a second-order antialiasing filter, a track- and-hold amplifier, a 14-bit
charge redistribution, successive approximation analog-to-digital converter
(ADC); a flexible digital filter; a 2.5 V reference and reference buffer; and high
speed serial and parallel interfaces. The AD7607 operates from a single 5 V
supply and can accommodate ±10 V and ±5 V true bipolar input signals while
sampling at throughput rates of up to 200 kSPS for all channels.
The input clamp protection circuitry can tolerate voltages of
up to ±16.5 V. The AD7607 has 1 MΩ analog input impedance, regardless of
sampling frequency. The single supply operation, on-chip filtering, and high input
impedance eliminate the need for driver op amps and external bipolar supplies.
The AD7607 antialiasing filter has a 3 dB cutoff frequency of 22 kHz and
provides 40 dB antialias rejection when sampling at 200 kSPS. The flexible
digital filter is pin driven and can be used to simplify external filtering.
6.9 Features ofAD7607:
1) ICAD7607 has 8 simultaneously sampled inputs, True bipolar analog input
ranges: (±10, ±5) V Single 5 V analog supply and 2.3 V to 5.25 V VDRIVE, Fully
integrated data acquisition solution.
2) Analog input clamp protection Input buffer with 1 MΩ analog input impedance
Second-order antialiasing analog filter On-chip accurate reference and reference
buffer 14-bit ADC with 200 KSPS on all channels.
3) Flexible parallel/serial interface SPI/QSPI™/MICROWIRE™/DSP compatible
Pin-compatible solutions from 14 bits to 18 bits Performance 7 kV ESD rating on
analog input channels.
4) Fast throughput rate: 200 kSPS for all channels 85.5 dB SNR at 50 kSPS INL
±0.25 LSB, DNL ±0.25 LSB.
5) Low power: 100 mW at 200 kSPS Standby mode: 25 mW typical 64-lead
LQFP package.
6.9.1 Applications of AD7607:
Power-line monitoring and protection systems Multiphase motor control
Instrumentation and control systems Multi axis positioning systems Data
acquisition systems (DAS).
6.9.2 Testing the ICAD7607:
To test the working condition of the ICAD7607, A simple trainer kit of two in
number is needed to give the digital inputs and analog input to the ICAD7607 and
corresponding digitals outputs can be obtained. Analog Supply Voltage of about
4.75 V to 5.25 V can be given to the ICAD7607. (i.eVcc) and supply voltage is
applied to the internal front-end amplifiers and to the ADC core. These supply
pins should be decoupled to AGND. All the AGND pins should be commonly
grounded (i.e AGND pins. whereas the analog ground should be given separately
grounded.
APPENDIX
EMBEDDED C PROGRAMME FOR dsPIC30F4011
#include <p30f4011.h>
# include <math.h>
#define VECTOR1 0X00 // 0 degrees
#define VECTOR2 0x2aaa // 60 degrees 0010 1010 1010 1010
#define VECTOR3 0x5555 // 120 degrees 0101 0101 0101 0101
#define VECTOR4 0x8000 // 180 degrees 1000 0000 0000 0000
#define VECTOR5 0xaaaa // 240 degrees 1010 1010 1010 1010
#define VECTOR6 0xd555 // 300 degrees 1101 0101 0101 0101
#define SIXTY_DEG 0x2aaa // 60 degrees 0010 1010 1010 1010
void pdc_update(void);
unsigned int fuzzylogic_voltage(unsigned int);
unsigned int fuzzylogic_angle(unsigned int);
void SVM(int , unsigned int );
int
sinetable[]__attribute__((far,section(".const,r")))={0,201,401,602,803,1003,1204,
1404,1605,1805,2005,2206,2406,2606,2806,3006,3205,3405,3605,3804,4003,420
2,4401,4600,4799,4997,5195,5393,5591,5789,5986,6183,6380,6577,6773,6970,7
166,7361,7557,7752,7947,8141,8335,8529,8723,8916,9109,9302,9494,9686,9877
,10068,10259,10449,10639,10829,11018,11207,11395,11583,11771,11958,12144
,12331,12516,12701,12886,13070,13254,13437,13620,13802,13984,14165,14346
,14526,14706,14885,15063,15241,15419,15595,15772,15947,16122,16297,16470
,16643,16816,16988,17159,17330,17500,17669,17838,18006,18173,18340,18506
,18671,18835,18999,19162,19325,19487,19647,19808,19967,20126,20284,20441
,20598,20753,20908,21062,21216,21368,21520,21671,21821,21970,22119,22266
,22413,22559,22704,22848,22992,23134,23276,23417,23557,23696,23834,23971
,24107,24243,24377,24511,24644,24776,24906,25036,25165,25293,25420,25547
,25672,25796,25919,26042,26163,26283,26403,26521,26638,26755,26870,26984
,27098,27210,27321,27431,27541,
27649,27756,27862,27967,28071,28174,28276,28377};
unsigned int t1,t2,tb=0,duty_r,duty_y,duty_b,ntv;
float t,f,f1,n,fslip,freq;
unsigned int voltage,theta=0,k,speed,slip;
float wref,vref,We,Ts,Vmag,mag1,mag,k1,s,Vll,fsli,fslip;
void initiate_all(void);
main ()
{
TRISB=0x0000;
PORTBbits.RB0=1; //for making adc work
initiate_all();
PTCONbits.PTEN=1; // PWM time base is ON
T3CONbits.TON=1; //timer C on
ADCON1bits.ADON=1; // A/D converter module is operating
ADCON1bits.SAMP=1; //At least one A/D sample/hold amplifier is sampling
IPC9bits.PWMIP=7; //Interrupt Priority Control Register 9/ 111= Interrupt is
priority 7 (highest priority interrupt)
while(1)
{
while(IFS0bits.T3IF==0); //if timer three interrupt flag is not set
while(!IFS0bits.ADIF); //ADC interrupt is set
{
k=ADCBUF0; //value taken from ADC buffer 0 is given to k
}
speed=k*0.977517;//for 5volts 1000 rpm,it implies that 1023 value is 1000..so
1000/1023 gives the actual speed
slip=(1000-speed)/1000;
freq=slip*50;
fslip=50-((6*freq)/120); //slip frequency
if(fslip<0)
{
ntv=1;
}
else
{
ntv=0;
}
wref=6.28*fslip;
IFS0bits.ADIF=0;
IFS0bits.T3IF=0;
vref=fuzzylogic_voltage(speed);
k1=wref*Ts*10430; // 2pi rad => 65535(2^16) rad
s=(long)k1;
Vmag=(vref*sqrt(2)*1.15470054)/250;
mag1=Vmag*32768; //Vmag is the returned value from fuzzy programme
mag=(long)mag1;
}
return 0;
}
void initiate_all()
{
TRISF=0x00; //port initialisation
PORTFbits.RF0=0; //taking port f bits as input
PORTFbits.RF1=0;
Ts =0.0002; // Sampling time = 2.5kHz
k1=We*Ts*10430; // 2pi rad => 65535(2^16) rad
s=(long)k1;
theta=fuzzylogic_angle(speed);
Vmag=(vref*sqrt(2)*1.15470054)/250;
mag1=Vmag*32768; //Vmag*2^15
mag=(long)mag1;
// ADC module //
//************************************************//
T3CON=0X0030; //1:256 prescalar value
PR3=0XFA8; //Period register with value FA8
TMR3=0; //32 bit module of timer register it is main significant bit…. PR3 is used
to compare from this register
IFS0bits.T3IF=0; //Timer 3 interrupt bit is cleared
ADPCFG=0x0000;
ADCON1=0x0040; //0000 0000 0100 0000//GP Timer3 compare ends sampling
and starts conversion
ADCON2=0x0000; //0000 0001 0000 0000// converts CH0
ADCON3=0x0707; //0000 0111 0000 0111// convertion clock select
bits_4*Tcy,7Tad
ADCHS=0x0000; //input select register, AN1 in CH0
ADCSSL=0x0000; //AN1in ch0
IFS0bits.ADIF=0; //clear the interrupt for ADC
// PWM Module //
//**********************************************//
PTCON = 0x0003; //up down counting mode.
PWMCON1 = 0x00FF; // Pulses with complimentary output
//DTCON1 = 0x0082; // prescalar 4, value= 3, therefore delay = tcy*4*3=2.4us
PWMCON2bits.IUE=1;
PTPER = 1000; // PWM period is .4msec
PTMR=0;
PDC1 =PTPER;
PDC2 =PTPER;
PDC3 =PTPER;
IFS2bits.PWMIF = 0;
IEC2bits.PWMIE=1;
tb=0;
}
unsigned int fuzzylogic_voltage(unsigned int speed)
{
unsigned int voltage;
if(speed>900)
{
voltage=20;
}
else if((speed>825)&&(speed<875))
{
voltage=40;
}
else if((speed>775)&&(speed<825))
{
voltage=46;
}
else if((speed>725)&&(speed<775))
{
voltage=60;
}
else if((speed>675)&&(speed<725))
{
voltage=110;
}
else if((speed>625)&&(speed<675))
{
voltage=113;
}
else if((speed>575)&&(speed<625))
{
voltage=125;
}
else if((speed>525)&&(speed<575))
{
voltage=155;
}
else if((speed>500)&&(speed<525))
{
voltage=170;
}
else if((speed>400)&&(speed<500))
{
voltage=190;
}
else if((speed>300)&&(speed<400))
{
voltage=215;
}
else if((speed>200)&&(speed<300))
{
voltage=246;
}
else
{
voltage=250;
}
return voltage;
}
unsigned int fuzzylogic_angle(unsigned int speed)
{
unsigned int angle_rotor;
if(speed>900)
{
angle_rotor=20;
}
else if((speed>825)&&(speed<875))
{
angle_rotor=40;
}
else if((speed>775)&&(speed<825))
{
angle_rotor=45;
}
else if((speed>725)&&(speed<775))
{
angle_rotor=61;
}
else if((speed>675)&&(speed<725))
{
angle_rotor=80;
}
else if((speed>625)&&(speed<675))
{
angle_rotor=85;
}
else if((speed>575)&&(speed<625))
{
angle_rotor=100;
}
else if((speed>525)&&(speed<575))
{
angle_rotor=110;
}
else if((speed>500)&&(speed<525))
{
angle_rotor=115;
}
else if((speed>400)&&(speed<500))
{
angle_rotor=119;
}
else if((speed>300)&&(speed<400))
{
angle_rotor=119;
}
else if((speed>200)&&(speed<300))
{
angle_rotor=119;
}
else
{
angle_rotor=119;
}
return angle_rotor;
}
void __attribute__((interrupt, no_auto_psv)) _PWMInterrupt (void)
{
if (theta >0xffff)
{
theta=0;//goes to beginning
}
SVM(mag,theta);
pdc_update();
theta=theta+s;
IFS2bits.PWMIF = 0;
}
void SVM(int mindx, unsigned int angle)
{
PORTFbits.RF1=1;
unsigned int angle1, angle2;
unsigned int half_t0,t1,t2,tpwm;
tpwm = 2000; //tpwm= Tsamp*2, *2 done for PDC, cos Actual PDC = PDC/2
if(mindx > 28300)
mindx = 28300;
if(angle < VECTOR2)
{
angle2 = angle - VECTOR1;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 1 (0 - 59 degrees)
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
else if(angle < VECTOR3)
{
angle2 = angle - VECTOR2;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 2 (60 - 119 degrees)
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
else if(angle < VECTOR4)
{
angle2 = angle - VECTOR3;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 3 (120 - 179 degrees)
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
else if(angle < VECTOR5)
{
angle2 = angle - VECTOR4;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 4 (180 - 239 degrees)
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
else if(angle < VECTOR6)
{
angle2 = angle - VECTOR5;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 5 (240 - 299 degrees)
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
else
{
angle2 = angle - VECTOR6;
angle1 = SIXTY_DEG - angle2;
t1 = sinetable[(unsigned char)(angle1 >> 6)];
t2 = sinetable[(unsigned char)(angle2 >> 6)];
t1 = ((long)t1*(long)mindx) >> 15;
t1 = ((long)t1*(long)tpwm) >> 15;
t2 = ((long)t2*(long)mindx) >> 15;
t2 = ((long)t2*(long)tpwm) >> 15;
half_t0 = (tpwm - t1 - t2) >> 1;
// Calculate duty cycles for Sector 6 ( 300 - 359 degrees )
duty_r = t1 + t2 + half_t0;
duty_y = t2 + half_t0;
duty_b= half_t0;
}
PORTFbits.RF1=0;
}
pdc_update()
{if(ntv==1)
{
PDC1=duty_r;
PDC2=duty_b;
PDC3=duty_y;
}
else
{
PDC1=duty_r;
PDC2=duty_y;
PDC3=duty_b;
}
}

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for printout

  • 1. DEVELOPMENT OF A VARIABLE SPEED PUMP USING DOUBLY FED INDUCTION MACHINE A PROJECT REPORT submitted by CB.EN.U4EEE10015 A.SURYA TEJA CB.EN.U4EEE10017 B.VISHAL CB.EN.U4EEE10035 L.NARAYANAREDDY CB.EN.U4EEE10057 S.VAMSI KRISHNA in partial fulfillment for the award of the degree of BACHELOR OF TECHNOLOGY IN ELECTRICAL AND ELECTRONICS ENGINEERING AMRITA SCHOOL OF ENGINEERING, COIMBATORE AMRITA VISHWA VIDYAPEETHAM AMRITANAGAR, COIMBATORE- 641112 May 2014
  • 2. AMRITA VISHWA VIDYAPEETHAM AMRITA SCHOOL OF ENGINEERING, COIMBATORE, 641112 BONAFIDE CERTIFICATE This is to certify that the project report entitled “Development of variable speed pumped hydro system using doubly fed induction machine” submitted by “A.SURYATEJA(EEE10015),B.VISHAL(EEE10017),L.NARAYANAREDDY(EEE10 035), S.VAMSIKRISHNA (EEE10057)” in partial fulfillment of the requirements for the award of the Degree Bachelor of Technology in “ELECTRICAL AND ELECTRONICS Engineering” is a bonafide record of the work carried out under my guidance and supervision at Amrita School of Engineering, Coimbatore. Mr. S. R.MOHANRAJAN Dr. K.C.SINDHU THAMPATTY SUPERVISOR CHAIRPERSON Assistant Professor (SG) Department of Electrical and Department of Electrical and Electronics Engineering, Electronics Engineering, Amrita School of Engineering, Amrita School of Engineering, Amrita Nagar, Coimbatore-641112 Amrita Nagar, Coimbatore-641112 This project report was evaluated by us on………. INTERNAL EXAMINER EXTERNAL EXAMINER
  • 3.
  • 4. ABSTRACT Effective integration of energy generating mechanism with energy storage will help in meeting the power demand at all times. Supply side management of power can be done using pumped storage systems. The best machine suited for this system is DFIM. This thesis is related to operating a DFIM in motoring mode to run a pump. The DFIM operates in motoring mode during low loads so that excess power is given to the storage system. Depending upon how much excess power is generated in the grid, the speed of the DFIM is set and the load of the pump varies according to pump characteristics. In this thesis, the DFIM was operated at all sub-synchronous speeds by using a fuzzy logic control mechanism. The control mechanism involves giving accurate voltages, angles and slip frequency to the rotor side of the machine to control the speed. Open loop test was done to get the relationship between speed and rotor voltage as well as speed and rotor angle. This was used in closed loop with a fuzzy logic controller.
  • 5. CONTENTS 1 . INTRODUCTION ...............................................................................................10 1.1 OBJECTIVE.................................................................................................12 1.1.1 The objectives include:........................................................................12 2 LITERATURE SURVEY..........................................................................................13 3 . STUDY STATE ANALYSISANDDYNAMICMODELLING OF DOUBLY FED INDUCTION MACHINE: 16 3.1 STEADY STATE ANALYSIS OF DOUBLY FED INDUCTION MACHINE: .................19 3.2 DYNAMIC MODELLING of DOUBLY FED INDUCTION MACHINE:.....................21 3.2.1 Features of Dynamic Modeling: ...........................................................21 3.2.2 Dynamic Modeling based on Space Vector Theory:...............................21 4 . SIMULATION....................................................................................................24 4.1 SIMULATION BLOCK DIAGRAM ...................................................................25 4.2 Input blocks:..............................................................................................26 4.3 Output measurement:................................................................................27 4.4 DESIGN OF FUZZY LOGIC CONTROLLER: ......................................................29 4.4.1 CALUCLATINGVALUES OF VOLTAGEMAGNITUDE ANDANGLE TO BE GIVEN TO ROTOR FOR DIFFERENT SPEEDS:.........................................................................29 4.5 BUILDING THE FUZZY INFERENCE SYSTEM: .................................................31 4.5.1 FIS Editor:...........................................................................................31 4.5.2 Membership Function Editor:..............................................................32 4.5.3 Rule Editor:........................................................................................35 4.6 SIMULATION RESULTS ...............................................................................36 4.7 INFERENCE:...............................................................................................42 5 . SOFTWARE DEVELOPMENT..............................................................................43 5.1 Introduction:..............................................................................................43 5.2 dsPIC30F4011 Digital Signal Microcontroller:...............................................44 5.3 Implementation of Control Algorithm:.........................................................44 5.4 Timer Circuit for ADC:.................................................................................44 5.5 Motor Control PWMmodule: .....................................................................45 5.6 ADC Module:.............................................................................................45 5.7 Implementation of Space Vector Algorithm:................................................46 5.8 Algorithm for SVPWM: ...............................................................................47 5.9 Flowchart:.................................................................................................48
  • 6. 5.10 Conclusion:................................................................................................49 6 . HARDWARE DESIGN.........................................................................................50 6.1 Introduction:.............................................................................................50 6.2 Current transducer:...................................................................................50 6.3 Voltage transducer:...................................................................................51 6.4 BI-QUAD FILTER.........................................................................................52 6.4.1 Application of bi-quad filter:...............................................................53 6.5 Precision rectifier:.....................................................................................53 6.6 Frequency to voltage converter: ................................................................54 6.7 Frequency multiplier: ................................................................................54 6.8 Analog to digital Conversion:.....................................................................55 6.9 Features of AD7607: ..................................................................................56 6.9.1 Applications of AD7607: .....................................................................56 6.9.2 Testing the ICAD7607: ........................................................................56
  • 7. LIST OF FIGURES Figure 3.1 Doubly Fed Induction Machine..................................................................16 Figure 3.2 Modes of operation of DFIM.....................................................................17 Figure 3.3 Steady State Equivalent Circuit of DFIM......................................................20 Figure 3.4 Dynamic Modeling equivalent circuit of DFIM.............................................22 Figure 4.1 Simulation of Block Diagram ......................................................................25 Figure 4.2 showing the speed input and torque being estimated for measuring the o/p mechanical power.......................................................................................................................26 Figure 4.3 Asynchronous Machine given input from both stator and rotor ...................26 Figure 4.4 showing the output parameters being measured........................................27 Figure 4.5 Power output measurement block .............................................................28 Figure 4.6 Subsystem developedfor giving pulses to the rotor side inverter.................28 Figure 4.7 Speed(X) Vs Voltage (Y)..............................................................................30 Figure 4.8 Speed(X) Vs Angle(Y) .................................................................................31 Figure 4.9 Mamdani System ......................................................................................32 Figure 4.10 Load Torque...........................................................................................33 Figure 4.11 Voltage...................................................................................................34 Figure 4.12 Angle.....................................................................................................35 Figure 4.13 Rules ......................................................................................................36 Figure 4.14 Rotor input speed....................................................................................38 Figure 4.15 rotor output speed..................................................................................38 Figure 4.16 Rotor torque output................................................................................39 Figure 4.17 Stator active power,rotoractive powerandmechanical power(fromtoptobottom) ................................................................................................................................39 Figure 4.18 Stator active power................................................................................40 Figure 4.19 Rotor active power..................................................................................41 Figure 4.20 Output Mechanical Power .......................................................................41 Figure 5.1 a) 3-phased balanced voltages b) resulting space vector...............................47 Figure 5.2 Flow Chart of the Programme....................................................................49 Figure 6.1 shows the circuit of LA-25NP current transducer.........................................50 Figure 6.2 shows the circuit of potential transducer....................................................52 Figure 6.3 shows a typical three-operational amplifier circuit......................................53 Figure 6.4 precision rectifier......................................................................................54 Figure 6.5 Frequency to voltage converter..................................................................54 Figure 6.6 Frequency Multiplier.................................................................................55 LIST OF TABLES Table 1 Speed voltage and Angle for fuzzylogic algorithm............................................29 Table 2 Closed Loop Simulation results.......................................................................36
  • 8. LIST OF SYMBOLS SYMBOLS DESCRIPTION UNIT Rs Stator Resistance Ω R Load Resistance Ω X Load Reactance Ω Xls Stator Leakage Reactance Ω Xlr’ Rotor Leakage Reactance Ω Rr’ Rotor Resistance Ω Xm’ Magnetizing Reactance Ω Ls Stator inductance H Lr Rotor inductance H Lm Mutual inductance H E Air gap voltage V s Slip a Stator to rotor turns ratio β Pitch angle Degre e ω Angular Frequency rad/s Vdc DC link Voltage V V Wind Speed m/s ρ Air density kg/ v Volume of air Cp Power coefficient A Rotor swept area Pt λ Turbine Power Tip speed ratio W
  • 9. Vds d axis stator voltage V Vqs Vdr Vqr P N ids iqs idr iqr Te Tm q axis rotor voltage d axis stator voltage q axis rotor voltage No of poles Speed of rotor Rotor electrical angular velocity Rotor angular velocity d axis stator current q axis rotor current d axis stator current q axis rotor current d axis stator flux q axis stator flux d axis rotor flux q axis rotor flux Stator real power Stator reactive power Rotor real power Rotor reactive power Stator current Stator equivalent or rotor current Stator Voltage Electrical torque Mechanical torque V V V rpm rad/s rad/s A A A A web web web web W W W W A A V Nm Nm
  • 10. 1 . INTRODUCTION The main essential characteristic of the grid is that the electric power generated should be equal to the energy demand at any time. If they are not equal, then there is a chance of loss of synchronization and it could lead to tripping of load and in worst cases, tripping of the grid itself. So there is a need for a sustainable technology that can meet the demand whenever needed. There is also a need of effective integration of new energy generating mechanism, its energy storage and transmission. All these together will improve not only the reliability of grid but also the cost incurred in meeting them. A storage system helps in improving the capability of system to provide energy when it is needed and store the energy whenever it is produced in excess. There are many energy storage technologies like Lead Acid Battery Storage and Lithium Ion Battery Storage, Superconducting Magnetic Energy Storage, Fly Wheel Storage and Pumped Hydro Systems (PHS). Among these the pumped hydro storage technology is found to be more optimal when storage capacity and efficiency were compared [1]. In future pumped hydro storage will stand alone as the most reliable technology available for grid power storage. In the past decade, there has been a tremendous increase in the wind and solar energy generation due to tax incentives and other policies. So developing the Pumped Hydro Storage plants near the places where there is a heavy chance of wind and solar energy generation can lead to improved grid reliability and it will reduce the need of additional fossil-fuelled generation. The characteristics like grid reliability are considered because of the reason that the wind blow is seasonal and solar energy is available only during daytime [3]. There is more demand for the development of energy storage systems as essential components for using renewable energy systems more efficiently and in large amounts. The variable speed pumped storage technology provides fast response in adjusting frequency regulation in both the generation and pumping. PHS is the least expensive method of energy storage as it does not require any
  • 11. additional fossil fuels for generating electricity. It is an emission free renewable resource. It is the best storage alternative while meeting the demand for bulk loads and is very quick in response. It is also having a high overall efficiency of about 70-80%. But these systems need lot of resources such as proper landscapes for installing the systems [4]. The main limitation of the PHS system is that it needs minimum one dam along the river streams or any water bodies that has a constant flow of water resources. So initiatives should be taken to implement the projects in sites where there will be minimal effects to the environment surrounding it. For that a feasibility study has to be done in those areas where the plant implementation is proposed. New approaches like locating reservoirs that are physically separated from existing river systems must be encouraged. Efforts should be taken to reduce the evaporation and seepage losses. There should be regular treatment to the Pumped Hydro Systems for better performance. But these systems will need less investment compared to flywheel, SMES, and battery storage technologies [5], [6]. In these plants, the energy is stored in the form of potential energy of water pumped up from a lower elevation reservoir to a higher elevation [7]. During periods of high electrical demand, the stored water is released through turbines to produce electric power by running an electrical machine (like Synchronous or Induction) in generating mode and during the process of pumping water from lower elevation to higher elevation, the electrical machine is operated in motoring mode [8],[9]. The motoring mode and generating mode can be achieved by either fixed or variable speed operations. The generating set operates at constant speed and during this fixed speed operation, power input is directly dependent upon the pumping head and cannot be adjusted. In variable speed operation, pump mode enables operation with adjustable power input at each of the required pumping head [10], [11], [12], thus providing regulated pump operation. Pump-turbine machines can be designed as fixed or variable speed machines. Presently in our project we have simulated a variable speed machine system using DFIM as machine. We only presented the motoring mode of the system i.e., connected to the pump.
  • 12. 1.1 OBJECTIVE The project proposes a new control scheme for running DFIM in motoring mode by connecting to a pump. The frequency and voltage for stator side are kept constant. The rotor speed is adjusted and based on the speed the rotor voltage and frequency is given to the rotor through fuzzy logic controller. 1.1.1 The objectives include:  Developing a DFIM system running at variable speed connected to a pump.  Simulation of the DFIM system using Matlab/SIMULINK for variable speeds by giving torque input using pump characteristics.  Implementation of control logic using dsPIC30f4011.
  • 13. 2 LITERATURE SURVEY [2.1] Andreas Oberhofer, “Energy Storage Technologies & Their Role in Renewable Integration,” Global Energy Network Institute, July 2012. “This paper presents an analysis on type of Energy Storage Techniques available and their advantages and disadvantages. It describes the advantages of Pumped Hydro Systems advantages over the other storage technologies. A critical observation is made on the benefits, problems and possible impacts in the future.” [2.2] Mahdi Johar, Ahmad Radan, Mohammad Reza Miveh and Sohrab Mirsaeidi, “Comparison of DFIG and Synchronous Machine for Storage Hydro- Power Generation”, International Journal of Pure and Applied Sciences and Technology, 3-10-11. “This paper deals with advantages and capabilities of variable speed storage – pumping plants. These features were compared with conventional synchronous ones in this paper. Different viewpoints such as structure and steady state behaviour are focused for comparing the application of Doubly Fed Induction Generators (DFIG) and synchronous ones in storage hydro plants. Dynamic stimulations are also used to evaluate the performance of variable- speed versus synchronous fixed-speed generation units.” [2.3] Rajib Datta and V. T. Ranganathan, “Variable-Speed Wind Power Generation Using Doubly Fed Wound Rotor Induction Machine-Comparison with Alternative Schemes,” IEEE Transactions on Energy Conversion, Vol. 17, No. 3, September 2002. “ In this paper the DFIM is connected to grid and is controlled from rotor side. The machine is compared in both fixed speed and variable speed systems using cage rotor induction machine. The comparison is made using the major hardware components required, energy output and operating region. This paper in detail explains the advantages and flexibility of variable speed systems compared to fixed speed systems. The DFIM is controlled from the rotor side in this paper. The speed is controlled by varying the supply on the rotor side and connecting the
  • 14. both rotor and stator to the grid. This paper shows that even though more simple and reliable, Fixed Speed Systems have some limitations. The energy capture can be increased significantly with connecting the DFIM for the variable speed system.” [2.4] P.Girihar Kini, “Effect of Voltage and Load Variations on Efficiencies of a Motor-Pump System”,IEEE transactions on energy conversions,Vol.25,N0.2, June 2010. “This paper deals with a three phase induction motor connected to a centrifugal pump model. In this model a DC motor is connected instead of pump to get the Induction machine system characteristics. This model shows that a DC machine can be used to replace the pump for determining the machine characteristics. The motor pump system is subjected to voltage and load variations to justify the system and for better result analysis.” [2.5] Xibo Yuan and Jianyun Chai, “A Converter-Based Starting Method and Speed Control of Doubly Fed Induction Machine with Centrifugal Loads”, IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 47, NO. 3, MAY/JUNE 2011. “This paper deals with the speed control of DFIM connected with a converter on the rotor side and rotor shaft connected to a centrifugal load. The paper presents the converter based starting method for running the induction machine with centrifugal loads. The machine is tested for variable speed operation. The machine is again connected to the DC machine for analysis. This paper explains the advantage of DFIM system connected to the pump.” [2.6] Dorin O. Neacsu, “SPACE VECTOR MODULATION –An Introduction,” The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001. “This is a tutorial presented by the author on the basics of Space Vector Pulse Width Modulation. The basics on Vectoral Analysis of Three Phase Converter, Pulse Width Modulation and Selection of the switching sequence were explained in detail. The Comparison is made on the different methods of generating
  • 15. SVPWM and the THD, Number of Switching States and dominant harmonics were analysed.” [2.7] Subrata.K.Mondal and Bimal.K.Bose, “Space Vector Pulse Width Modulation of Three-Level Inverter Extending Operation Into Overmodulation Region,” IEEE transactions on Power Electronics, Vol.18, No.2, March 2003. This Paper deals with the Space Vector Pulse Width Technique and it’s over modulation and under modulation methods. The paper deals with Space Vector PWM and its control algorithm for DSP based implementation. The voltage and angle were given as inputs to the algorithm and it creates SVPWM pulses using it at 1.0 kHz switching frequency. In this method the switching states are distributed such that the neutral point voltage always remains balanced. An open loop V/f controlled induction motor drive has been evaluated using both over modulated and under modulated strategies by giving the voltage and frequency in whole speed range.”
  • 16. 3 . STUDY STATE ANALYSIS AND DYNAMIC MODELLING OF DOUBLY FED INDUCTION MACHINE: Figure 3.1 Doubly Fed Induction Machine DFIM is a Wound Rotor Induction Machine with AC supply given to both stator and rotor. The PWM back to back inverter is connected to the rotor side. The main advantage of this system is the capability of rotor circuit in allowing the bidirectional flow of power in both sub-synchronous mode and super-synchronous mode [21]. The power rating of the converter is also reduced as it is connected to the rotor side. It is to note that the number of turns in stator should be more than the number of turns in the rotor [24]. With the voltage reduction in the rotor side, it is possible to operate at a lower DC bus voltage. Consequently the voltage ratings for the devices and the capacitor bank can be optimized [25]. So, for the same power rating, the power generated by this system is higher compared to other systems. Its speed range is very high. It can run both in sub synchronous mode and super synchronous mode based on the requirement [26], [27].
  • 17. Figure 3.2 Modes of operation of DFIM Variable speed operation is having more advantages than fixed speed for large scale turbine. The main advantage of the DFIM is that the power processed by the power converter is only the slip power, it is only a fraction of total power. If it is operated within a speed range preferably around the synchronous speed, then the power converter rating can be reduced drastically. This is more advantageous for centrifugal loads as pumps. The speed limit is set by the rating of the converter we deploy in the system. If it goes beyond this speed then the converter loses control. So it will have a little problem in starting. To solve this problem, starting resistors or autotransformers can be used. It is applicable to PHS as the system is having apparatus of high capacity. In a grid controlled DFIM system, the voltage and frequency are imposed by the grid. So, the active power and reactive power control should be taken care of. If it is made to run as stand- alone, voltage and frequency should also be regulated. The active and reactive power flow control is the main concept behind the control methods. The active
  • 18. and reactive power oscillations of DFIM under voltage sag are very less and are only for fraction of seconds. If the reference reactive power is set then the reactive power suddenly increases and then reduces to the rated value. Even the DC link voltage will oscillate for some time and settles quickly. When the grid voltage reduces, the rotor flux also gets reduced. Under voltage swell i.e., when voltage is increased to more than rated value the active power again oscillates and settles at rated value. The reactive power suddenly reduces and comes to the rated value. Compared to the Synchronous machine and Induction machine drives, DFIM has better efficiency. It does not require high rating power converters as they can be connected to the rotor side with half the power rating [30], [31]. They have better dynamic stability than the other machines under variable speed operation. The time taken for them to convert from motor to generator is less compared to other machines. The amount of power generated using the same size machine for DFIM will be more compared to other machines [32]. During motor condition in sub-synchronous mode, the rotor generates power and in super synchronous mode, it absorbs power. In generator condition the rotor absorbs power at sub synchronous mode and produces power in super synchronous mode. When comparing the dynamic behavior the factors voltage drop test, testing for torque perturbations, behavior of the systems based on inter area oscillations are considered[33]. When compared the synchronous machine has less voltage drop and the variable speed machine DFIM has high voltage drop but the time taken to stabilize the active power and reactive power is less. In case of torque disturbances the variable speed has more advantage than the fixed speed as the change in torque is stabilized by the change in the speed which has to compensate by power flow control in synchronous machine [34]. In a variable speed system the torque disturbances will never be a problem. The synchronous machine provides good damping for active power oscillations only until certain frequency while the variable speed machine provides good damping for a better frequency range. With or without Power System Stabilizer, the behavior of reactive power and stator voltage are similar. If we consider reactive power, the behavior of synchronous and variable speed machines fluctuates for different frequency
  • 19. ranges. For one frequency range, one machine behaves better than the other. For a lower frequency range, the variable speed machine has better behavior because it has constant amplitude. For a higher frequency range, the synchronous machine has better behavior. Compared to DFIG with same speed and power, a synchronous machine has smaller dimensions and inertia with a larger air gap. With lesser rotor current, DFIG can generate same active and reactive power as a synchronous machine. So, synchronous machine is not as cost effective as DFIG. 3.1 STEADY STATE ANALYSIS OF DOUBLY FED INDUCTION MACHINE: The steady state analysis of DFIM consists of equivalent circuit of it. In this circuit  It is assumed that both the stator and the rotor are connected in the star configuration; however, only one phase of the stator and rotor three- phase windings is represented.  The stator is supplied by the grid at constant and balanced three- phase AC voltage amplitude and frequency.  The rotor is supplied also at constant and balanced AC voltage amplitude and frequency, independently from the stator, for instance, by a back-to-back voltage source converter.  To represent steady state voltage and current magnitudes, the analysis is carried out using classical phasor theory: [1]_DFIG Vs = supply stator voltage Vr = supply rotor voltage Is = induced Stator Current Ir = induced rotor current Es = induced EMF in the stator Ers= induced emf in the rotor  The equivalent circuit of DFIM is
  • 20. Figure 3.3 Steady State Equivalent Circuit of DFIM So when representing the equivalent circuit the equation w.r.t is given by 𝑉𝑟 𝑠 − 𝐸𝑠 = ( 𝑅 𝑟 𝑠 + 𝑗𝑤𝑠𝐿 𝑟)𝐼𝑟 𝑎𝑡 𝑓𝑠 By this equation we can understand that the injected voltage on the rotor side can be determined if the rotor current and stator voltage are known at a particular slip. The rotor voltage is given by 𝑉2𝑝 ′ = 𝐸 + 𝐼2𝑝 ′ ( 𝑅2 𝑠 + 𝑗𝑋2) 𝓋2𝑝 = 𝑉2𝑝 ′ ( 𝑠 𝑎 ) 𝑤. 𝑟. 𝑡 𝑠𝑡𝑎𝑡𝑜𝑟 The rotor current and frequency are given by 𝐼2𝑝 = 𝑎𝐼2𝑝′ 𝑓𝑟 = 𝑓𝑠 − ( 𝑃𝑁 120 ) The real power and reactive power supplied to the load were given by 𝑝1 = 3𝑅𝑒(𝑉1𝑝 𝐼1𝑝 ∗ ) 𝑞1 = 3𝐼𝑚(𝑉1𝑝 𝐼1𝑝 ∗ )
  • 21. The real power and reactive power supplied to the load from rotor were given by 𝑝2 = ±3𝑅𝑒(𝑉2𝑝 𝐼2𝑝 ∗ ) 𝑞2 = 3𝐼𝑚(𝑉2𝑝 𝐼2𝑝 ∗ ) The output mechanical power is given by 𝑝 𝑚 = 3𝐼2𝑝 2 𝑅2 ( 1 − 𝑠 𝑠 ) − 𝑝2 ( 1 − 𝑠 𝑠 ) 3.2 DYNAMIC MODELLING of DOUBLY FED INDUCTION MACHINE: 3.2.1 Features of Dynamic Modeling:  Dynamic Modeling explains and defines the behavior of the machine’s variables in transition periods as well as in the steady state.  By means of the dynamic model it is possible to know at all times the continuous performance of the variables of the machine, such as torque, currents, and fluxes.  In this way, by using the information provided by the dynamic model, it is possible to know how the transition from one state to another is going to be achieved, allowing one to detect unsafe behaviors, such as instabilities or high transient currents.  The dynamic model also provides additional information of the system during the steady state operation, such as dynamic oscillations, torque or current ripples. 3.2.2 Dynamic Modeling based on Space Vector Theory: It is represented in general in differential equation form, is often structured as a compact set of model equations.
  • 22.  The DFIM equivalent electric circuit is shown below,  Figure 3.4 Dynamic Modeling equivalent circuit of DFIM  The instantaneous stator voltages, current and fluxes of the machine can be described by the following electric equations 𝑣 𝑎𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑎𝑠( 𝑡) + 𝑑𝜓𝑎𝑠 (𝑡) 𝑑𝑡 𝑣 𝑏𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑏𝑠( 𝑡) + 𝑑𝜓 𝑏𝑠(𝑡) 𝑑𝑡 𝑣𝑐𝑠( 𝑡) = 𝑅 𝑠 𝑖 𝑐𝑠( 𝑡)+ 𝑑𝜓𝑐𝑠 (𝑡) 𝑑𝑡 Rs is the stator resistance; ias(t), ibs(t) and ics(t) are the stator currents of phases a, b, and c; vas(t), vbs(t), and vcs(t) are the applied stator voltages; and cas(t), cbs(t), and ccs(t) are the stator fluxes  The rotor magnitudes are described by the following equations. Here, Rr is the rotor resistance referred to the stator; iar(t), ibr(t), and icr(t) are the stator referred rotor currents of phases a, b and c; var(t), vbr(t) and vcr(t)
  • 23. are the stator referred rotor voltages; and car(t), cbr(t) and ccr(t) are the rotor fluxes. 𝑣 𝑎𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑎𝑟( 𝑡) + 𝑑𝜓𝑎𝑟 (𝑡) 𝑑𝑡 𝑣 𝑏𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑏𝑟( 𝑡) + 𝑑𝜓 𝑏𝑟 (𝑡) 𝑑𝑡 𝑣𝑐𝑟( 𝑡) = 𝑅 𝑟 𝑖 𝑐𝑟( 𝑡) + 𝑑𝜓𝑐𝑟(𝑡) 𝑑𝑡  Alpha-beta Model: the voltage equations of the DFIM in space vector form: 𝑣⃗ 𝑠 𝑠 = 𝑅 𝑠 𝑖⃗𝑠 𝑠 + 𝑑𝜓⃗⃗ 𝑠 𝑠 𝑑𝑡 𝑣⃗ 𝑟 𝑟 = 𝑅 𝑟 𝑖⃗𝑟 𝑟 + 𝑑𝜓⃗⃗𝑟 𝑟 𝑑𝑡  superscripts “s” and “r” indicate that space vectors are referred to stator and rotor reference frames, respectively and the correlation between the fluxes and the currents, in space vector notation, is given by the following equation where Ls and Lr are the stator and rotor inductances, Lm is the magnetizing inductance 𝜓⃗⃗𝑠 𝑠 = 𝐿 𝑠 𝑖⃗𝑠 𝑠 + 𝐿 𝑚 𝑖⃗𝑟 𝑠 𝜓⃗⃗ 𝑟 𝑟 = 𝐿 𝑚 𝑖⃗𝑠 𝑟 + 𝐿 𝑟 𝑖⃗𝑟 𝑟 For transforming all equations into stator reference frame we use the equation Now the equations become: 𝑣⃗ 𝑠 𝑠 = 𝑅 𝑠 𝑖⃗𝑠 𝑠 + 𝑑𝜓⃗⃗ 𝑠 𝑠 𝑑𝑡 𝑣⃗ 𝑟 𝑠 = 𝑅 𝑟 𝑖⃗𝑟 𝑠 + 𝑑𝜓⃗⃗𝑟 𝑠 𝑑𝑡 − 𝑗𝜔 𝑚 𝜓⃗⃗𝑟 𝑠 𝜓⃗⃗𝑠 𝑠 = 𝐿 𝑠 𝑖⃗𝑠 𝑠 + 𝐿 𝑚 𝑖⃗𝑟 𝑠 𝜓⃗⃗𝑟 𝑠 = 𝐿 𝑚 𝑖⃗𝑠 𝑠 + 𝐿 𝑟 𝑖⃗𝑟 𝑠
  • 24. 4 . SIMULATION The Simulation of the DFIM is made using the MATLAB/SIMULINK. The machine speed and torque are given as input. The speed and torque are related by the pump characteristics as torque is proportional to square of speed. Torque is given positive and the machine runs as motor. The main objective is to obtain different speeds for different torque values and optimize the power taken out from the grid. So the speed reference is given to the machine based on the power available on the grid. So the frequency of grid helps in giving this parameter. The parameters that required for simulation are measured by doing no load test and block rotor test on the machine. The parameters are found to be  Power Output (VA): 1100VA  Voltage Line to Line: 415 V  Frequency: 50Hz  R stator =6.4Ω ; L stator= 0.183H  R rotor =9.8903Ω ; L rotor =0.0224H  L mutual = 0.208H Pole pairs = 3. The figure shown below is the Simulink model of the simulation. It consists of a three phase asynchronous induction machine connected to the inverter. The voltage is injected on the rotor side by giving the Space Vector Pulse Width Modulation (SVPWM) pulses. The machine parameters are fed to the asynchronous machine model and a fuzzy control method is used to control the machine speed for different voltage and slip frequencies injected to the rotor. The speed parameter is given as input to the machine and voltage and angle to be injected to the rotor are obtained by fuzzy logic control. Then these parameters are fed to the SVPWM generator. The generated pulses are fed to inverter as pulses and the desired voltage and slip frequency values are produced. The torque and power are measured by power measuring blocks. The total mechanical power should be equal to sum of rotor and stator input power which is
  • 25. observed in simulation. This method will provide a new method of controlling speed with optimizing power loss. 4.1 SIMULATION BLOCK DIAGRAM Figure 4.1 Simulation of Block Diagram
  • 26. 4.2 Input blocks: Figure 4.2 showing the speed input and torque being estimated for measuring the o/p mechanical power. The speed is first converted to rad/sec to the rotor side of the machine and the torque input is estimated from the sped input and is given by the equation T= (0.957870572e-3)*N2. Where N is speed and T is Torque. Figure 4.3 Asynchronous Machine given input from both stator and rotor
  • 27. The stator side is supplied from the three phase AC source and the rotor side is supplied from the inverter. The inverter is fed from a DC source. When the machine runs in sub-synchronous motor operation then the rotor will give out the power which is proportional to the slip of the machine. And the rotor supply is at slip frequency. The DC voltage given in the system is 80V (but given the turns ratio the voltage is given as 715 volts). The supply given to the rotor side from the inverter is given with slip frequency fs. Where fs=(f-fr). Where fr is frequency of rotation of rotor. 4.3 Output measurement: Figure 4.4 showing the output parameters being measured The parameters needed to be measured are selected from bus selector that is given to the measurement pin of machine. The rotor currents, Electromagnetic torque, Speed and Rotor angle are measured from it.
  • 28. Figure 4.5 Power output measurement block For measuring the instantaneous active and reactive power . The blocks will give the mean value of power when the 3-phase voltage and power are given to it. The rotor and stator real and reactive power are measured by the blocks as shown in Fig.6. The blocks will give the mean value of power when the 3-phase voltage and power are given to it. Figure 4.6 Subsystem developed for giving pulses to the rotor side inverter
  • 29. After measuring the rotor voltage angle and slip frequency through the control loop the parameters are given to a VVVF source and the voltage, instantaneous angle is measured with PLL and given to the ABC to DQ conversion block and from there to Alpha-Beta then to pulses generator. Thus the pulses are generated and given to the inverter on the rotor side. 4.4 Design of Fuzzy Logic Controller: To control the Doubly Fed Induction Machine by using a set of predefined rules obtained from open-loop test, a fuzzy inference system can be used. Fuzzy inference process helps in formulating the mapping from a given input to an output using fuzzy logic. Here, Mamdani-type fuzzy inference system is used. 4.4.1 Calculating Values of Voltage Magnitude and Angle to be Given to Rotor For Different Speeds: For designing the fuzzy logic controller, we need to know the values of inputs and outputs to be given and taken from the fuzzy inference system. Here the input is speed reference and outputs are voltage magnitude and voltage angle which are to be given to the rotor. The magnitude and angles are given to the rotor along with slip frequency. Speed of the rotor depends to a large extent on the slip frequency given to the rotor. Through trial and error, the values of voltage and angle were found for approximately 20 different slip values using open loop test. Table 1 Speed voltage and Angle for fuzzylogic algorithm SPEED (rpm) VOLTAGE MAGNITUDE(V) VOLTAGE ANGLE 900 20 20 850 40 40 800 46 45 750 60 61 700 110 80 650 113 85
  • 30. 600 125 100 550 155 110 500 170 115 450 180 117 400 190 119 350 200 119 300 215 119 200 246 119 The relation between speed and voltage is found to be linear. Figure 4.7 Speed(X) Vs Voltage (Y) The relation between speed and angle is linear for higher values of speed. For lower values of speed, the angle required to be given is almost constant.
  • 31. Figure 4.8 Speed(X) Vs Angle(Y) Now that the inputs and outputs are found out, the fuzzy inference system can be designed which can take any value between 0 and 1000 as speed reference input and it can generate corresponding voltages and angles. 4.5 BUILDING THE FUZZY INFERENCE SYSTEM: The graphical tools which were used to build and edit fuzzy inference system are: 1. Fuzzy Inference System (FIS) Editor 2. Membership Function Editor 3. Rule Editor 4.5.1 FIS Editor: This editor displays information about fuzzy inference system. Here, we use a 1 input and 2 output system. The input is load in terms of speed and outputs are voltage magnitude and voltage angle to be given to sub-system which generates reference signals for inverter.
  • 32. Figure 4.9 Mamdani System 4.5.2 Membership Function Editor: The membership functions associated with all input and output variables of the fuzzy system can be edited here. The membership function type chosen for load torque is trapezoidal type. For voltage and angle the membership function type chosen is Gaussian. Here, the load torque being in terms of speed is split into 16 membership functions with a range from 0 to 1000. The voltage is in the range of 0 to 300 while the angle is in the range of 0 to 120. Any changes in membership functions are reflected in the rules. Based on the values obtained in the open loop test, the membership functions are edited so that every input from 0 to 1000 can be mapped to a certain voltage output and angle output by using if-then rules. The membership functions for load torque, voltage and angle are shown below.
  • 33. Figure 4.10 Load Torque For example, let us consider the membership function with the name as 850. This membership function takes all values between 825 and 875. Similarly, membership function with name 500 takes all values from 475 to 525. The membership functions used here are trapezoidal membership functions. The membership functions are made to overlap each other. This is because, if overlapping is not done, the border values give wrong results when used in simulation.
  • 34. Figure 4.11 Voltage For voltage and angle, the membership functions used here are gaussian membership functions. The angle varies from 20 degrees to 119 degrees proportionally with slip and voltage increases from 20V to 277V for slip varying from 0.1 to 0.9. Also the magnitude of voltage generated is same for all values in a particular membership function. Similarly the magnitude of angle generated is also same for a particular membership function. So make the behavior linear, we need to use more membership functions. This helps in making the result piecewise linear.
  • 35. Figure 4.12 Angle 4.5.3 Rule Editor: Based on the open-loop test values, all the inputs can be mapped to corresponding outputs by using the if-then rules. The rule editor is shown below. Each membership function is labelled by its peak value. This makes the rule editing easier.
  • 36. Figure 4.13 Rules Now, the fuzzy inference system is designed. It is then exported to Matlab workspace and used in Simulink. 4.6 SIMULATION RESULTS The simulationistestedbyusingastep-loadinput varying from 0 to 10 N-m. The load is given in terms of speed. For this variable load, the rotor speed, stator power, rotor power, mechanical power and rotor torque are plotted. The results are shown below. Table 2 Closed Loop Simulation results SPEED (rpm) VOLTAGE MAGNITUDE(V) VOLTAGE ANGLE STATOR ACTIVE POWER(W) ROTOR ACTIVE POWER(W) 900 20 20 110 -90
  • 37. 850 40 40 960 -53 800 46 45 920 -97 750 60 61 855 -112 700 110 80 630 -142.5 650 113 85 560 -210 600 125 100 500 -230 550 155 110 400 -290 500 170 115 350 -310 450 180 117 305 -290 400 190 119 290 -260 350 200 119 280 -195 300 215 119 250 -175 200 246 119 200 -147
  • 38. Figure 4.14 Rotor input speed Figure 4.15 rotor output speed
  • 39. Figure 4.16 Rotor torque output Figure 4.17 Stator active power, rotor active power and mechanical power (from top to bottom)
  • 40. Figure 4.18 Stator active power
  • 41. Figure 4.19 Rotor active power Figure 4.20 Output Mechanical Power
  • 42. 4.7 INFERENCE: 1. Rotor speed increases proportionally with the increase in load. As the slip frequency varies, rotor speed varies according to the value of slip frequency given to the rotor. 2. Stator active power and mechanical power also increase with the increase in load. 3. Rotor power, being directly proportionally to slip and stator active power will decrease in magnitude as the load increases. This is because as load increases, slip decreases. 4. But for lower values of load, the rotor power behaves differently because the value of stator active power is very low. 5. Rotor torque increases proportionally with increase in load. 6. For operating Doubly Fed Induction Machine with a pump, the machine must run at a speed proportional to the load on the pump because torque of the pump is directly proportional to the square of the speed. Here the speed control is done according to pump characteristics. 7. For higher load torque on the pump, we run the DFIM at higher speed and vice versa.
  • 43. 5 . SOFTWARE DEVELOPMENT 5.1 Introduction: The coding for the digital signal processor is done in MPLAB IDE v8.46 from Microchip Technology Inc. The programming was done in C platform. For this MPLAB has a language tool suite add-on called MPLAB C30 compiler. The complete standard C library is provided with the MPLAB C compiler for dsPIC DSCs. MPLAB allows the user to view certain waveforms in its logic analyser like PWM, port outputs etc. Also different types of inputs can be given to the simulator using stimulus by register injection, clock stimulus, asynchronous stimulus etc. The register values can be viewed through watch window. The code is converted to hex file format after compiling and the dsPIC30F4011 DSC is programmed using LabProg IC programmer. For implementing control algorithm of DFIG the timer modules, ADC module and PWM modules are used. In order to implement the control algorithm for DFIG the code for the project is divided into different modules. The ADC module and PWM modules were tested independently using the clock stimulus and the logic analyser which is available in the MPLAB. Finally the complete program for implementing the control algorithm is done by clubbing all the individual programs. The different sections of the program are as follows:  A frequency control algorithm for determining the output frequency of the PWM.  A voltage control algorithm for fixing the output voltage magnitude  PWM module for generating the SVPWM pulses  Fuzzy logic programme for generating voltage and angle with a particular speed  Different timer modules for co-ordinating different peripherals.
  • 44. 5.2 dsPIC30F4011Digital Signal Microcontroller: It is a 16 bit high performance digital signal controller which uses Modified Harvard Architecture. The C Compiler optimized instruction set architecture with flexible addressing modes. It is having 83 Base Instructions. Each instruction is 24-bit wide, 16-bit wide data path. The main speciality of dsPIC30f4011 is 24 Kbytes On-Chip Flash Program Space (8K instruction words) which is very efficient in storing the look up tables. it is possible to use DC to 40 MHz external clock input. But in our purpose we are using 20MHz crystal oscillator to give external clock input. So each instruction will take .2 micro seconds execution time. There are 12 peripherals and 29 interrupt sources are available in the controller. We can assign priority to different interrupt sources. Among these peripherals the peripherals used for implementing the control algorithm for DFIG includes the following.  I/O Ports  Timers  10-bit A/D Converter  Motor control PWM module  UART Module 5.3 Implementation of Control Algorithm:  Initially the value of speed is given by a anolog pin to channel CH0 from AN1.  Then with fuzzylogic the voltage and angle for that particular speed is estimated.  This voltage and angle value will be fed to SVPWM control algorithm made in the programme to provide six inverter pulses. 5.4 Timer Circuit for ADC: The device has got 5 16bit timers, which can be operated either in timer mode or in counter mode. The one of the important feature of these timers are that it can be operated in pairs, so that we will get 32bit count. In this work two timers are used here.Timer1 is used to update the PDC and Timer3 to update the value to the
  • 45. ADC.Timer1 is configured to operate for 0.3ms to update the PDC register Timer2 is configured to operate for .8ms to trigger the ADC module. The flow chart for ADC sampling process is given in the figure. The TxCON and PRx are the registers which need to be configured while doing programming with the timers. 5.5 Motor Control PWM module: The dsPIC30F4011 has a dedicated peripheral module for generating PWM pulses, called the MCPWM module. The device has got 3 PWM modules with 2 PWM pins per module. The PWM pins can be configured to work in independent mode or in complimentary mode. In this work it is configured to operate in complimentary mode. A programmable dead time generator is also present to introduce sufficient dead time when working in complimentary mode. In this work a dead time of 3μsec is used. The MCPWM module can be operated in different modes like free-running mode, edge triggered mode, centre aligned mode, up-down counting mode etc. In this work up-down counting mode is chosen. The switching frequency of SPWM is 2.5 kHz. The PWM module is configured to operate at this frequency. The count to be loaded for this in PTPER register is calculated as follows 5.6 ADC Module: The10-bit high-speed analog-to-digital converter (A/D) allows conversion of an analog input signal to a 10-bit digital number. This module is based on a successive approximation register (SAR) architecture, and provides a maximum sampling rate of 500 ksps. The A/D module has 16 analog inputs which are multiplexed into four sample and hold amplifiers. The output of the sample and hold is the input into the converter, which generates the result. The A/D module is having six 16 bit configuration registers which includes ADCON1, DCON2,ADCON3, ADPCFG, ADCHS, ADCSSL.
  • 46. For the closed loop control algorithm for the DFIG, both the speed as well as the stator voltage references is giving to the ADC pins in terms of analog values. AN0 pin holds the speed reference and AN1 pin holds the stator voltage reference. A sampling time of .8mSec is used for sampling. Simultaneous sampling is enabled by configuring the ADCON1 register, so that timing complications will be eliminated. The conversion and sampling is configured to automatic mode. That is internal counter ends sampling and the next sampling starts immediately after previous conversion. Interrupts are generated after every 2nd sample/covert sequence. A/D conversion clock is set to 2Tcy = 0.1μs. The sampled values will be stored in ADCBUF0&ADCBUF1 registers. The result of the ADC is a 10 bit digital value. Since the reference voltage to the ADC is 5V, therefore when a 5V analog signal is detected then the result stored in the ADC buffer will be 1023 (2^10 – 1). Hence when x voltage is detected, then the value of x can be obtained as, x*(1000/1023). Here the value needed is from 0 to 1000 as this value is given for varying speed. 5.7 Implementation of SpaceVector Algorithm: Space vector pulse width modulation technique was used for the switching of SEMIKRON inverter in this project due to the following merits.  High DC link voltage utilisation.  Very much suited for digital implementation  Reduced harmonics and losses. The space vector modulation technique is somewhat similar to the Sine+3rd harmonic PWM technique but the method of implementation is different. Similar to the rotating magnetic field in the case of 3 phase machines, that is if a three phase balanced voltage is applied to the windings of a three-phase machine, a rotating voltage space vector may be talked of. The resultant voltage
  • 47. space-vector will be rotating uniformly at the synchronous speed and will have a magnitude equal to 1.5 times the peak magnitude of the phase voltage. Each vector corresponds to a switching state, at that state we will obtain the corresponding voltage magnitude at the 3phase output as mentioned in the fig 5.5(a). The intermediate magnitudes will obtained by the combination of the fundamental switching states. The fundamental frequency can be adjusted by adjusting the angular velocity of the vector. The phase sequence of the output voltage can be controlled by changing the direction of rotation of the vector. Both are very important as far as this project is concern. Figure 5.1 a) 3-phased balanced voltages b) resulting space vector 5.8 Algorithm for SVPWM: 1. First find out the input dc link voltage (Edc), desired output frequency ‘f OP’ desired phase sequence of output voltage, desired magnitude of output voltage and the desired switching frequency. During each sampling time period three switching take place, where one turn-on and one turn-off is taken as one switching. 2. Calculate magnitude factor ‘α’ from the knowledge of input dc link voltage and the desired output voltage. α Edc= 3/2 times peak of phase voltage. (5.4.a) 3. Also calculate the sampling time period TS= 1/(3 fSW) (5.4.b)
  • 48. 4. Initialize sector position = I, and angle ‘θ’ = 0. Assume the rotating space voltage vector to remain stalled at this position for the sampling time period ‘TS’. Calculate the time duration for active and null state vectors by the equations. 5. Output the inverter switching pulses as per the calculated time durations so as to realize the space vectors in the following sequence: V (111), V1(101), V2(100), V7(000). 6. Calculate the next position angle = + 2 for clockwise rotation, and = − 2 for anti-clockwise rotation. Recalculate the time durations as in step (3) above but this time the switching sequence will be V7(000), V2(100), V1(101), V8(111). 7. Step (4) is to be repeated but every time the switching sequence alternates between the sequences given in steps 4 and 5. When the space vector enters sector-II (θ ≥ π/3), the vector is replace by V2 and V2 is replaced by V3. The process continues to produce a continuously rotating voltage space vector of fixed magnitude and fixed speed 5.9 Flowchart: The flow chart algorithm is presented below
  • 49. Figure 5.2 Flow Chart of the Programme 5.10 Conclusion: Coding of the controller was performed in MPLAB. The output pulses were observed in logic analyser. Both the fundamental voltage and frequency are varying precisely with the references given in the ADC pin of the dsPIC.
  • 50. 6 . HARDWARE DESIGN 6.1 Introduction: This part of the project work describes hardware control circuit design both for controlling the stator voltage and frequency of the DFIG. potential transducer is designed for 500V line voltage and a current transducer of 25A is designed in order to obtain the rotor current and the values obtained after the design are standardized. 6.2 Current transducer: Current transducer is generally used for the electronic measurements of currents: DC, AC, pulsed mixed with a galvanic isolation between the primary circuit and the secondary circuit. Current transducer is preferred usually due to its added features and advantages like accuracy, linearity, low temperature drift, optimized response time, wide frequency band width, no insertion losses, high immunity to external interference and also due to its current over load capability. So for the above features and advantages the current transducer that best suites is LA 25-NP for which the primary current nominal is in the range of (5-25) A. Based on the data sheet of LA 25-NP design is done and explained below. Figure: 1.1 Figure 6.1 shows the circuit of LA-25NP current transducer
  • 51. The relation between the turn’s ratio and the currents is given below 𝐓. 𝐑 = 𝐧 = 𝐍𝐩 𝐍𝐬 = 𝐈𝐬 𝐈𝐩 Is = Ip ( Np Ns ) Where the turn’s ratio is decided based on the recommended connections stated in the data sheet. From the above diagram primary current (IP) *(1/1000) = IS 25*1.414*(1/1000) = IS =0.0353A 2.5v = IS*RM RM = 2.5/0.0353= 70.82 ohms 6.3 Voltage transducer: The pic cannot withstand DFIG stator voltage directly. The input that is given to the pic should be in the range of (0-5) v. So the stator voltage of DFIG has to be scaled down to 5v. For that we need the potential transformer. In this project, we need to convert a 500V to a 2.5V. So we selected the potential transformer LV- 20P. As per the data sheet of the potential transformer the primary current of the PT should not exceed 10mA. So it is essential to introduce a power resistor in the primary circuit to limit the primary current. The design procedure of the potential transformer is given below. The PT is designed for maximum of 500V input voltage Maximum allowable primary current in PT=10mA. So the value of the resistor that has to be added to the primary circuit is known from the current and the voltage values stated above
  • 52. Input resistance to the PT = 94kΩ (standardized value) Input current =500/94k= 5.319mA PT turns ratio (n) =2500:1000 Secondary current =5.319mA*2.5=13.297mA=0.01329A Secondary rms voltage=2.5/1.414=1.7677V Measuring resistance needed= 133.0Ω The connection diagram of the PT is shown below and the measuring Resistance is selected in such a way that the maximum potential drop across the secondary should be 2.5V Figure: 1.2 Figure 6.2 shows the circuit of potential transducer 6.4 BI-QUAD FILTER The bi-quad configuration is a useful circuit for producing band pass and low-pass responses, whereas the bi-quad and the state variable filter circuit configuration can have Q-factor values of 400 or greater and at high frequencies operation of bi- quad filter gives an efficient way of filtering the responses of the various inputs given. So in this project bi-quad filter is used to filter the voltage response taken from the speed of the rotor.
  • 53. Figure: 2.1 Figure 6.3 shows a typical three-operational amplifier circuit 6.4.1 Application of bi-quad filter: 1) It is easily tunable using single resistor tuning (normally a stereo or ganged potentiometer). 2) It can be configured to produce a Butterworth or a Chebychev response by changing the damping (1/Q) 6.5 Precisionrectifier: A simple rectifier circuit uses a diode and there is a turn on voltage for the diode. The input voltage has to exceed the turn on voltage (0.6v for ordinary si diode) before rectification is achieved. A precision rectifier is an active circuit using an op amp and a diode in the feedback loop. This over comes the turn on Knee voltage. The op amp reduces the turn –on voltage of a diode in its feedback loop by a factor equal to the open loop gain of the op amp. For practical op amp gains this reduces the forward voltage to a fraction of mv. Thus giving a precision rectifier or near ideal diode characteristic for the rectifier function. This is how a precision rectifier circuit differs from the simple rectifier circuit. In this project the voltage pulses taken from the bi-quad filter is rectified by using precision rectifier circuit. Figure 2.2
  • 54. Figure 6.4 precision rectifier 6.6 Frequency to voltage converter: The rectified input from the precision rectifier is given to the frequency to voltage converter. Now the voltage-to-frequency converter provides an output frequency accurately proportional to its input voltage. Figure2.3 Figure 6.5 Frequency to voltage converter 6.7 Frequency multiplier: A frequency multiplier has the property that the frequency of the output signal has an integer multiple of the input frequency. Based on this property the frequency input from the converter circuit is given to the frequency multiplier to get desired frequency.
  • 55. Figure 2.4 Figure 6.6 Frequency Multiplier 6.8 Analog to digital Conversion: The AD76071 is a 14-bit, simultaneous sampling, analog- to- digital data acquisition system (DAS). The part contains analog input clamp protection; a second-order antialiasing filter, a track- and-hold amplifier, a 14-bit charge redistribution, successive approximation analog-to-digital converter (ADC); a flexible digital filter; a 2.5 V reference and reference buffer; and high speed serial and parallel interfaces. The AD7607 operates from a single 5 V supply and can accommodate ±10 V and ±5 V true bipolar input signals while sampling at throughput rates of up to 200 kSPS for all channels. The input clamp protection circuitry can tolerate voltages of up to ±16.5 V. The AD7607 has 1 MΩ analog input impedance, regardless of sampling frequency. The single supply operation, on-chip filtering, and high input impedance eliminate the need for driver op amps and external bipolar supplies. The AD7607 antialiasing filter has a 3 dB cutoff frequency of 22 kHz and
  • 56. provides 40 dB antialias rejection when sampling at 200 kSPS. The flexible digital filter is pin driven and can be used to simplify external filtering. 6.9 Features ofAD7607: 1) ICAD7607 has 8 simultaneously sampled inputs, True bipolar analog input ranges: (±10, ±5) V Single 5 V analog supply and 2.3 V to 5.25 V VDRIVE, Fully integrated data acquisition solution. 2) Analog input clamp protection Input buffer with 1 MΩ analog input impedance Second-order antialiasing analog filter On-chip accurate reference and reference buffer 14-bit ADC with 200 KSPS on all channels. 3) Flexible parallel/serial interface SPI/QSPI™/MICROWIRE™/DSP compatible Pin-compatible solutions from 14 bits to 18 bits Performance 7 kV ESD rating on analog input channels. 4) Fast throughput rate: 200 kSPS for all channels 85.5 dB SNR at 50 kSPS INL ±0.25 LSB, DNL ±0.25 LSB. 5) Low power: 100 mW at 200 kSPS Standby mode: 25 mW typical 64-lead LQFP package. 6.9.1 Applications of AD7607: Power-line monitoring and protection systems Multiphase motor control Instrumentation and control systems Multi axis positioning systems Data acquisition systems (DAS). 6.9.2 Testing the ICAD7607: To test the working condition of the ICAD7607, A simple trainer kit of two in number is needed to give the digital inputs and analog input to the ICAD7607 and corresponding digitals outputs can be obtained. Analog Supply Voltage of about 4.75 V to 5.25 V can be given to the ICAD7607. (i.eVcc) and supply voltage is applied to the internal front-end amplifiers and to the ADC core. These supply pins should be decoupled to AGND. All the AGND pins should be commonly grounded (i.e AGND pins. whereas the analog ground should be given separately grounded.
  • 57. APPENDIX EMBEDDED C PROGRAMME FOR dsPIC30F4011 #include <p30f4011.h> # include <math.h> #define VECTOR1 0X00 // 0 degrees #define VECTOR2 0x2aaa // 60 degrees 0010 1010 1010 1010 #define VECTOR3 0x5555 // 120 degrees 0101 0101 0101 0101 #define VECTOR4 0x8000 // 180 degrees 1000 0000 0000 0000 #define VECTOR5 0xaaaa // 240 degrees 1010 1010 1010 1010 #define VECTOR6 0xd555 // 300 degrees 1101 0101 0101 0101 #define SIXTY_DEG 0x2aaa // 60 degrees 0010 1010 1010 1010 void pdc_update(void); unsigned int fuzzylogic_voltage(unsigned int); unsigned int fuzzylogic_angle(unsigned int); void SVM(int , unsigned int ); int sinetable[]__attribute__((far,section(".const,r")))={0,201,401,602,803,1003,1204, 1404,1605,1805,2005,2206,2406,2606,2806,3006,3205,3405,3605,3804,4003,420 2,4401,4600,4799,4997,5195,5393,5591,5789,5986,6183,6380,6577,6773,6970,7 166,7361,7557,7752,7947,8141,8335,8529,8723,8916,9109,9302,9494,9686,9877 ,10068,10259,10449,10639,10829,11018,11207,11395,11583,11771,11958,12144 ,12331,12516,12701,12886,13070,13254,13437,13620,13802,13984,14165,14346 ,14526,14706,14885,15063,15241,15419,15595,15772,15947,16122,16297,16470 ,16643,16816,16988,17159,17330,17500,17669,17838,18006,18173,18340,18506 ,18671,18835,18999,19162,19325,19487,19647,19808,19967,20126,20284,20441 ,20598,20753,20908,21062,21216,21368,21520,21671,21821,21970,22119,22266
  • 58. ,22413,22559,22704,22848,22992,23134,23276,23417,23557,23696,23834,23971 ,24107,24243,24377,24511,24644,24776,24906,25036,25165,25293,25420,25547 ,25672,25796,25919,26042,26163,26283,26403,26521,26638,26755,26870,26984 ,27098,27210,27321,27431,27541, 27649,27756,27862,27967,28071,28174,28276,28377}; unsigned int t1,t2,tb=0,duty_r,duty_y,duty_b,ntv; float t,f,f1,n,fslip,freq; unsigned int voltage,theta=0,k,speed,slip; float wref,vref,We,Ts,Vmag,mag1,mag,k1,s,Vll,fsli,fslip; void initiate_all(void); main () { TRISB=0x0000; PORTBbits.RB0=1; //for making adc work initiate_all(); PTCONbits.PTEN=1; // PWM time base is ON T3CONbits.TON=1; //timer C on ADCON1bits.ADON=1; // A/D converter module is operating ADCON1bits.SAMP=1; //At least one A/D sample/hold amplifier is sampling IPC9bits.PWMIP=7; //Interrupt Priority Control Register 9/ 111= Interrupt is priority 7 (highest priority interrupt) while(1) {
  • 59. while(IFS0bits.T3IF==0); //if timer three interrupt flag is not set while(!IFS0bits.ADIF); //ADC interrupt is set { k=ADCBUF0; //value taken from ADC buffer 0 is given to k } speed=k*0.977517;//for 5volts 1000 rpm,it implies that 1023 value is 1000..so 1000/1023 gives the actual speed slip=(1000-speed)/1000; freq=slip*50; fslip=50-((6*freq)/120); //slip frequency if(fslip<0) { ntv=1; } else { ntv=0; } wref=6.28*fslip; IFS0bits.ADIF=0; IFS0bits.T3IF=0; vref=fuzzylogic_voltage(speed);
  • 60. k1=wref*Ts*10430; // 2pi rad => 65535(2^16) rad s=(long)k1; Vmag=(vref*sqrt(2)*1.15470054)/250; mag1=Vmag*32768; //Vmag is the returned value from fuzzy programme mag=(long)mag1; } return 0; } void initiate_all() { TRISF=0x00; //port initialisation PORTFbits.RF0=0; //taking port f bits as input PORTFbits.RF1=0; Ts =0.0002; // Sampling time = 2.5kHz k1=We*Ts*10430; // 2pi rad => 65535(2^16) rad s=(long)k1; theta=fuzzylogic_angle(speed); Vmag=(vref*sqrt(2)*1.15470054)/250; mag1=Vmag*32768; //Vmag*2^15 mag=(long)mag1; // ADC module // //************************************************// T3CON=0X0030; //1:256 prescalar value
  • 61. PR3=0XFA8; //Period register with value FA8 TMR3=0; //32 bit module of timer register it is main significant bit…. PR3 is used to compare from this register IFS0bits.T3IF=0; //Timer 3 interrupt bit is cleared ADPCFG=0x0000; ADCON1=0x0040; //0000 0000 0100 0000//GP Timer3 compare ends sampling and starts conversion ADCON2=0x0000; //0000 0001 0000 0000// converts CH0 ADCON3=0x0707; //0000 0111 0000 0111// convertion clock select bits_4*Tcy,7Tad ADCHS=0x0000; //input select register, AN1 in CH0 ADCSSL=0x0000; //AN1in ch0 IFS0bits.ADIF=0; //clear the interrupt for ADC // PWM Module // //**********************************************// PTCON = 0x0003; //up down counting mode. PWMCON1 = 0x00FF; // Pulses with complimentary output //DTCON1 = 0x0082; // prescalar 4, value= 3, therefore delay = tcy*4*3=2.4us PWMCON2bits.IUE=1; PTPER = 1000; // PWM period is .4msec PTMR=0; PDC1 =PTPER; PDC2 =PTPER; PDC3 =PTPER;
  • 62. IFS2bits.PWMIF = 0; IEC2bits.PWMIE=1; tb=0; } unsigned int fuzzylogic_voltage(unsigned int speed) { unsigned int voltage; if(speed>900) { voltage=20; } else if((speed>825)&&(speed<875)) { voltage=40; } else if((speed>775)&&(speed<825)) { voltage=46; } else if((speed>725)&&(speed<775)) { voltage=60; }
  • 63. else if((speed>675)&&(speed<725)) { voltage=110; } else if((speed>625)&&(speed<675)) { voltage=113; } else if((speed>575)&&(speed<625)) { voltage=125; } else if((speed>525)&&(speed<575)) { voltage=155; } else if((speed>500)&&(speed<525)) { voltage=170; } else if((speed>400)&&(speed<500)) { voltage=190;
  • 64. } else if((speed>300)&&(speed<400)) { voltage=215; } else if((speed>200)&&(speed<300)) { voltage=246; } else { voltage=250; } return voltage; } unsigned int fuzzylogic_angle(unsigned int speed) { unsigned int angle_rotor; if(speed>900) { angle_rotor=20; }
  • 65. else if((speed>825)&&(speed<875)) { angle_rotor=40; } else if((speed>775)&&(speed<825)) { angle_rotor=45; } else if((speed>725)&&(speed<775)) { angle_rotor=61; } else if((speed>675)&&(speed<725)) { angle_rotor=80; } else if((speed>625)&&(speed<675)) { angle_rotor=85; } else if((speed>575)&&(speed<625)) { angle_rotor=100;
  • 66. } else if((speed>525)&&(speed<575)) { angle_rotor=110; } else if((speed>500)&&(speed<525)) { angle_rotor=115; } else if((speed>400)&&(speed<500)) { angle_rotor=119; } else if((speed>300)&&(speed<400)) { angle_rotor=119; } else if((speed>200)&&(speed<300)) { angle_rotor=119; } else {
  • 67. angle_rotor=119; } return angle_rotor; } void __attribute__((interrupt, no_auto_psv)) _PWMInterrupt (void) { if (theta >0xffff) { theta=0;//goes to beginning } SVM(mag,theta); pdc_update(); theta=theta+s; IFS2bits.PWMIF = 0; } void SVM(int mindx, unsigned int angle) { PORTFbits.RF1=1; unsigned int angle1, angle2; unsigned int half_t0,t1,t2,tpwm; tpwm = 2000; //tpwm= Tsamp*2, *2 done for PDC, cos Actual PDC = PDC/2 if(mindx > 28300)
  • 68. mindx = 28300; if(angle < VECTOR2) { angle2 = angle - VECTOR1; angle1 = SIXTY_DEG - angle2; t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)]; t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1; // Calculate duty cycles for Sector 1 (0 - 59 degrees) duty_r = t1 + t2 + half_t0; duty_y = t2 + half_t0; duty_b= half_t0; } else if(angle < VECTOR3) { angle2 = angle - VECTOR2; angle1 = SIXTY_DEG - angle2; t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)];
  • 69. t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1; // Calculate duty cycles for Sector 2 (60 - 119 degrees) duty_r = t1 + t2 + half_t0; duty_y = t2 + half_t0; duty_b= half_t0; } else if(angle < VECTOR4) { angle2 = angle - VECTOR3; angle1 = SIXTY_DEG - angle2; t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)]; t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1; // Calculate duty cycles for Sector 3 (120 - 179 degrees) duty_r = t1 + t2 + half_t0;
  • 70. duty_y = t2 + half_t0; duty_b= half_t0; } else if(angle < VECTOR5) { angle2 = angle - VECTOR4; angle1 = SIXTY_DEG - angle2; t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)]; t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1; // Calculate duty cycles for Sector 4 (180 - 239 degrees) duty_r = t1 + t2 + half_t0; duty_y = t2 + half_t0; duty_b= half_t0; } else if(angle < VECTOR6) { angle2 = angle - VECTOR5; angle1 = SIXTY_DEG - angle2;
  • 71. t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)]; t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1; // Calculate duty cycles for Sector 5 (240 - 299 degrees) duty_r = t1 + t2 + half_t0; duty_y = t2 + half_t0; duty_b= half_t0; } else { angle2 = angle - VECTOR6; angle1 = SIXTY_DEG - angle2; t1 = sinetable[(unsigned char)(angle1 >> 6)]; t2 = sinetable[(unsigned char)(angle2 >> 6)]; t1 = ((long)t1*(long)mindx) >> 15; t1 = ((long)t1*(long)tpwm) >> 15; t2 = ((long)t2*(long)mindx) >> 15; t2 = ((long)t2*(long)tpwm) >> 15; half_t0 = (tpwm - t1 - t2) >> 1;
  • 72. // Calculate duty cycles for Sector 6 ( 300 - 359 degrees ) duty_r = t1 + t2 + half_t0; duty_y = t2 + half_t0; duty_b= half_t0; } PORTFbits.RF1=0; } pdc_update() {if(ntv==1) { PDC1=duty_r; PDC2=duty_b; PDC3=duty_y; } else { PDC1=duty_r; PDC2=duty_y; PDC3=duty_b; } }