fuzzy mppt and dtc control of a photovoltaic water...
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Fuzzy MPPT and DTC Control of a photovoltaic
Water Pumping System
A.Lazizi
M.Kesraoui
A. Chaib Faculty of Hydrocarbons and
Chemistry
Applied Automation laboratory
University of Boumerdes, Algeria
Faculty of Hydrocarbons and
Chemistry
Applied Automation laboratory
University of Boumerdes, Algeria
Faculty of Hydrocarbons and
Chemistry
Applied Automation laboratory
University of Boumerdes, Algeria
Abstract— In this paper we aim to find a better control of
photovoltaic water pumping system. The photovoltaic
module can provide a maximum power only for defined
output voltage and current. In addition, the operation to
get the maximum power depends on the terminals of load,
mostly a nonlinear load like induction motor. In this
work, we use fuzzy logic method for the maximum power
point tracking of a photovoltaic system. The system
includes solar module, a DC / DC converter equipped with
its MPPT control, DC/AC inverter and a centrifugal pump
driven by a three phase induction motor. In order to
control the flow of the centrifugal pump, a Direct Torque
Control - DTC of the induction machine is used. To
illustrate the performances of the control, simulation
results are carried out using Matlab/Simulink.
Keywords—photovoltaic generator ,MPPT, DTC control,
fuzzy logic.
I. INTRODUCTION
Water resources are essential for satisfying human
needs, protecting health, and ensuring food production
especially in isolated regions and rural remote areas
because generally the grid network is not present, therefore,
it is necessary to look for other energy resources to fulfill
their energy requirements. Photovoltaic pumping systems
(PVPS) seems to be a suitable application of photovoltaic
energy sources to fill this lack of energy. The use of these
systems is growing rapidly nowadays because of their
interesting characteristics such as, excellent reliability, long
life, ease of installation, autonomy of working and low
maintenance [1, 2, 9] . PV water pumping systems generally consist of PV generator, controller, inverter,
motor and pump [8].
It is well known that the main problem posed by the use
of PV generator is their non-linear nature. The energy
extracted from the PV array is dependent of the climatic
conditions.
In fact, such module has an optimum operating point,
called the Maximum Power Point (MPP), numerous
methods for MPPT are proposed to be implemented in the
PV system ,such as perturbation and observation (P&O)
,incremental conductance(INC) ,voltage feedback methods
,and so on ,fuzzy logic control (FLC) ,neural network,
genetic algorithm. The P&O and INC methods are commonly used in the MPPT system because of their
simple implementation. However, the P&O method has two
drawbacks regarding its performance. The first is power
oscillation at the maximum power point (MPP) and the
other one is divergence of the MPP under atmospheric
change. The problem of power oscillation of the MPP also
occurs with the INC method when fast tracking of the
maximum power is desired. [12, 13]
A number of experimental DC motor driven PV pumps
are already in use in several parts of the word. However
their major drawback is the presence of brushes which increase the probability of maintenance and their high costs.
Hence a pumping system based on an induction motor (IM)
can be more attractive. This kind of motors has been
adopted due to its low cost and the low maintenance
requirements. In addition, the increased efficiency of solar
pumping systems makes this latter particularly attractive,
even more the additional cost of the inverter is less
significant. In recent years, the advent of efficient inverter
to control the speed of these motors has allowed their use
for solar pumping applications. [1, 2, 4]
Pump used is the centrifugal type driven by a three phase asynchronous motor which is powered by a three-
phase inverter. To control the water flow, it is therefore
necessary to establish a system for monitoring the speed of
the drive motor. Scalar and vector control are used in [7,
10, 11], is a cheap, well-implementable method but it’s not
satisfactory for the control of drives with dynamic behavior,
since it gives a slow response to transients. In this paper, in
order to improve energy conversion efficiency, an
intelligent control technique using fuzzy logic control is
associated to an MPPT controller and the method of Direct
Torque Control (DTC) is used to control the flow of the
centrifugal pump.
II. MODELING OF WATER PUMPING SYSTEM
The PV water pumping system considered in this work
is shown in Fig.1.It consist of PV generator, asynchronous
machine and a centrifugal pump.
MPPT
DC
DC
Solar panel
PW
M
DC
AC
PUMP
I.M
DTC
control
Fig.1. structure of water pumping system
A. Solar Cell Model
Photovoltaic cell is the most basic generation part in PV
system. In the literature several models of the PV cell are
found (one diode, two or three diodes).
They differ from each other by the number of
parameters involved in the calculation of the voltage and
current of the PV final.
The model for a single diode is the most cited in the
literature consists of a photo current source, a diode, an
equivalent parallel resistor and an equivalent series resistor
which can be shown in Fig.2.[12]
Rsh
Rs
Iph
Ish Id
V
I
DV
Fig.2.Equivalent circuit of solar cell
So we can mathematically express the current produced
by the solar cell as:
(1)
The mathematic relationship for the current and voltage in the single diode equivalent circuit can be
described as:
: The voltage at the terminal of the cell (in volt).
: Light-generated current or photocurrent.
: Cell saturation of dark current.
: Diode current.
: Shunt resistance.
: Series resistance.
: The electron charge . : Boltzman constant : Absolute temperature (in Kelvin).
: Junction ideality factor.
: Diode saturation curent.
The parameters chosen for modeling corresponds to the
PV module are listed in Tab.1
TABLE.1 CHARACTÉRISTICS OF THE PV MODULE
Parameter Value
Maximum power ( ) 200W
Voltage at Pmax 26.3V
Current at Pmax ( ) 7.61 A
Open circuit voltage ( ) 32.9 V
Short-circuit current ( ) 8.21 A
Short circuit curent/Temperature coefficient 3.18e-3
Open circuit voltage/Temperature coefficient -0.123
No. of cells 54
B. DC/DC boost converter
A boost converter is a step-up DC to DC converter .The
operation of the boost converter is fairly simple, with an
input capacitor inductor and switch (usually
MOSFET) and output capacitor .The power switch is
responsible to modulate the energy transfer from the input
source to the load by varying the duty cycle .
The classical relationship between input and output
voltage of a boost converter operating at steady state
condition is given by:
(3)
: Output voltage.
: Input voltage.
: Duty cycle.
The electrical circuit of a boost converter is shown in Fig.3.
L
Cin
+
_
Vi
+
_
Vo
IL ID
Icout
iout
icin
Iin
IsVL + _
Cout Vs
Fig.3.Boost Converter Circuit
C. Induction motor modeling
The equivalent circuit of the induction motor is
illustrated by Fig.4.
Rs
Is
Vs Es Xm
Xls
Ism
XlrIr
Rr
Fig.4.Equivalent circuit of the induction motor
The dynamic model of induction motor expressed in the
rotating coordinate system can be represented by a 4 sets of equation: [1, 10, 11]
Voltage equations:
(4)
Flux equations:
(5)
Torque equation:
(6)
Finally, the dynamic equation is written as:
(7)
The parameters chosen for modeling corresponds to the
induction machine are listed in Tab.2
TABELE.2 INDUTION MACHINE CHARACTERISTIC
Parameter Value
rated power 2238
number of pole pairs 2 stator resistance 0.435 rotor resistance 0816 Statoric cyclic inductance 2e-3 Rotoric cyclic inductance 2e-3
Mutual cyclic inductance 69.31e-3
Inertia 0.089 Friction coefficient 0.005
D. Centrifugal pump modeling
The hydraulic output power of the pump can be
characterized by: [1, 2, 10, 11]
(8)
Where:
: The water flow rate
: The total head
The relation between the hydraulic output power Pp of
the Pump and the mechanical input power Pm can be
defined as the pump efficiency and is given by:
(9)
The load torque of the centrifugal pump can be
described by:
(10)
The parameters chosen for modeling corresponds to the
centrifugal pump are listed in Tab.3
TABELE.2 CENTRIFUGAL PUMP PARAMETERS
Parameter Value
Pump effeciency 90%
Total pump head 80
III. FUZZY LOGIC MPPT CONTROLLER
Recently fuzzy logic controllers have been introduced in
the tracking of the MPP in PV systems. They have the
advantage to being robust and relatively simple to design as
they do not require the knowledge of the exact model. They
do require in the other hand the complete knowledge of the
operation of the PV system by the designer.
A fuzzy logic controller basically includes –
Fuzzification, Rule base, Inference method and
Defuzzification method. [12, 13]
The proposed fuzzy logic based MPPT controller has two
inputs are error and change in error and one output,
change in duty cycle The input variables are defined by:
(11)
(12)
Where and is the instant power and voltage of
the boost converter. [8]. Fig.5.represents the fuzzy logic
controller.
Fig5.Fuzzy Logic Controller
The input and output variables are converted into
linguistic variables .In this case, five fuzzy subsets,
(Negative Big), (NegativeSmall), (Equal
Zero), (Positive Big), (Positive Small) have been chosen.
The PV system output power and the efficiency using
fuzzy logic controller considers that the solar irradiance is
1000 and the temperature is are shown in Fig.6 and Fig.7.
Fig.6. PV System Output Power with FLC MPPT When Is Constant
Fig.7. PV efficiency with FLC MPPT Is Constant
In stable conditions the simulation of the PV system shows the effectiveness of the Fuzzy Logic MPPT
Controller, since it becomes constant at the maximum value
after a small stilling time.
When the solar irradiance is variable and the
temperature is kept constant . The curve of power and
efficiency of the PV module are given by the Fig. 8 and
Fig.9.
Fig.8.PV System Output Power With FLC MPPT When Is variable
Fig.9. PV Efficiency with FLC MPPT When Is variable
The FLC has good performances such as rapidity
and damping of the overshoot.
E. Direct Torque control of the IM
In order to have an adjustable flow rate of the pump, we
propose a control system of induction motor based on the
method of Direct Torque Control, DTC. The main features
of this method can be summarized a direct control of flux
and torque by selecting the optimum inverter switching
vectors, this method is characterized by its simple
implementation and a fast dynamic response.
The stator flux and torque estimation are presented by:
(13)
(14)
(15)
(16)
The basic functional blocks used to implement the DTC
scheme are represented in Fig.10
Lo
ok-u
p t
ab
le
Flux
comparators
Torque
comparators
Concordia transformation
Flux and Torque estimator
M-
+
-+
iabc
iαβ vαβ
vabc
ϴs Cm
Cm*
Q*s
Qs
Fig.10.DTC scheme for ac motor
IV. SIMULATIONS RESULTS
We took the starting value of as the
reference speed of the induction motor .At time , a
step change in the reference speed to a speed of
is caused. Then to a speed of at
The value of irradiance and temperature are kept
respectively at 1000 W/m2 and c25 . Simulation results are
given in the following figures.
Fig.11.The stator current
Fig.12.The rotor current
Fig.13.The water flow rate
The strategy of Direct Torque Control served here
as a way to control the flow of the pumping station. It
improves the stator current signal. But its drawback is a
small ripple in the flow rate due to the use of a comparator
with hysteresis at two levels.
Fig.14.The motor electromagnetic torque
As shown in Fig.14 the electromagnetic torque
tracks the value of the reference and this method allows
reducing ripple of the electromagnetic torque.
Fig.15.The motor speed
Simulation results are satisfactory. Indeed, the motor speed tracks the value of the reference speed desired.
V. CONCLUSION
In this paper, we studied a control structure using both
the concept of Direct Torque Control (DTC) method for
induction motor and the operation at MPPT for the DC-DC
converter to improve efficiency of PV pumping systems.
A PV system with an intelligent maximum power point
tracker (MPPT) has been modeled using a DC/DC boost
converter to maintain the constant output power of the load
at maximum point in variable solar irradiation. This controller was tested using MATLAB/SIMULINK.. From
the results it was clearly proved that the FLC has a very
good performance. It reduces the time response of the PV
system and also it eliminates the fluctuations around the
maximum power point. The use of FLC can improve the
efficiency of the overall system by minimizing the energy
losses when the irradiation is variable. The results of the
direct torque control of the induction machine has shown
that great performances was achieved, fast responses with
no overshoot and less fluctuations in the steady state. The
introduction of DTC in PV systems is very promising.
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