Photovol ta ic Sy stem s using PSIM
Sol a r Cha rg e Controllll l er to im prove the effic ienc y of Sta nda l one
Desig n & Im pl em enta tion of va rious MPPT Al g orithm s for
A PROJECT REPORT
Submitted by
ARUMUGAM.R (97408105701)
KUTHALINGAM.C (97408105022)
PATTUSELVAM .S (97408105035)
THIRUVENGADAM.M (97408105059)
In partial fulfillment for the award of the degree
of
BACHELOR OF ENGINEERING
in
ELECTRICAL AND ELECTRONICS ENGINEERING
GOVERNMENT COLLEGE OF ENGINEERING,
TIRUNELVELI-627007
ANNA UNIVERSITY ::CHENNAI 600 025
APRIL 2012
a l one Photovolta ic Sy stem s using PSIM
MPPT a l g orithm s for Sol a r Cha rg e Controll l er to im prove the effic ienc y of Sta nd -
Desig n & Im pl em enta tion of va rious
BONAFIDE CERTIFICATE
Certified that this project report “
” is the Bonafide work of
ARUMUGAM.R (97408105701),KUTHALINGAM.C (97408105022),
PATTUSELVAM .S (97408105035),THIRUVENGADAM.M (97408105059) , who
carried out the project work under my supervision.
SUPERVISOR HEAD OF THE DEPARTMENT
Controlll l er to im prove the effic ienc y of Sta nd - a l one Photovol ta ic Sy stem s using PSIM
Desig n & Im pl em enta tion of va rious MPPT a l g orithm s for Sol a r Cha rg e
CERTIFICATE OF EVALUATION
Government College Of Engineering, Tirunelveli-7
Electrical and Electronics Engineering.
Submitted by
ARUMUGAM.R (97408105701)
KUTHALINGAM.C (97408105022)
PATTUSELVAM .S (97408105035)
THIRUVENGADAM.M (97408105059)
Done under the supervision of
Prof. INDRA GETZY DAVID, M.E.,
The reports of the project work submitted by the above students in partial
fulfillment for the award of Bachelor of Engineering Degree in Electrical and
Electronics Engineering, Anna University Chennai were confirmed and evaluated.
Submitted for the Anna University Examinations held at Government College
of Engineering, Tirunelveli - 7 on 18.04.2012
INTERNAL EXAMINER EXTERNAL EXAMINER
ACKNOWLEDGEMENT
Our first and foremost praises and thanks to God, the almighty for his valuable
grace upon us to complete this project.
We submit our sincere thanks to our Principal
Dr.V. LAKSHMI PRABHA., Head of the Institution, Government College of
Engineering, Tirunelveli who showed a deep solitude on all of us regarding this
project work. With great pride and immense pleasure we express our deep sense of
gratitude and profound thanks to Prof .INDRA GETZY DAVID, M.E., Head of the
Department, Electrical and Electronics Engineering, Government College of
Engineering, Tirunelveli, for encouraging us to undertake the project work and who
was an instrumental brain behind this project.
We extend our special thanks to Superintending Engineer Auto Substation
Muthaiyapuram,Tuticorin for permitting us for a visit during power apparatus testing.
Next we express our sincere thanks to our faculty advisor
Mrs.M.GNANA SUNDARI,M.E, Asst.professor of EEE for leading us in the way
of completion of this project. We also express our sincere thanks to all the faculty
members of Department of Electrical and Electronics Engineering for their co-
operation in completing this project.
We also offer special thanks to our parents who have sacrificed greatly in making
this project possible. We thank all those who have helped directly and indirectly in our
project.
TABLE OF CONTENTS
CHAPTER TITLE PAGE
NO
LIST OF TABLES (i)
LIST OF FIGURES
(ii)
1
2
3
INTRODUCTION
PV ARRAY MODELLING
2.1 Photovoltaic modules
2.2 Equivalent circuit of a solar cell
2.3 Open circuit voltage, short circuit current and
maximum power point
2.4 Fill Factor
2.5 Temperature and irradiance effects
SOLAR CHARGE CONTROLLER
3.1 MPPT based solar charge controller
3.2 Converter choice for MPPT
3.3 Boost converter
3.3.1 Mode1 operation of boost converter
3.3.2 Mode2 operation of boost converter
1
5
6
7
8
9
10
15
16
17
17
18
19
4
5
MAXIMUM POWER POINT TRACKING
ALGORITHM
4.1 An overview of maximum power point
tracking
4.2 Different MPPT techniques
4.2.1 Perturb and Observe
4.2.2 Incremental conductance method
SIMULATION AND EVALUATION
5.1 PSIM
5.2 Circuit structure
5.3 Solar cell models
5.4 Simulation model of Perturb & Observe
algorithm for MPPT
5.5 Limitations of Perturb & Observe method
5.6 Simulation model of incremental
conductance method for MPPT
5.7 Analysis & discussions of Simulation
results
5.8 Conclusion
21
22
24
24
28
34
35
36
37
39
41
42
43
47
This project describes a method for obtaining optimal power from a
ABSTRACT
small PV panel with maximum power point techniques. In an age of dwindling
fossil fuels and climate change a lot of attention is being been focused on
renewable forms of energy such as photovoltaic (PV) cells.
The Photovoltaic cell is
a semiconducting device that absorbs light and converts it into electrical energy in
the form of DC.
The
DC power extracted from the PV array is synthesized and
modulated
by the converter to suit the load requirements.
In
general, PV system
consists of a PV array, solar charge controller, rechargeable battery, solar inverter
and loads. The aim of this project work is to study the design of Solar Charge
Controller using various Maximum Power Point Tracking Algorithms. Further, the
various design techniques are simulated in
the Power SIM Software Environment
and their strengths and weakness are evaluated.
Solar Charge Controller to improve the efficiency of Standalone
Photovoltaic System using PSIM
Design & Implementation of various MPPT Algorithms for
CHAPTER – I
INTRODUCTION
“We believe that the clean and inexhaustible power of sunlight will be the most
promising resource in mankind's quest to develop sustainable energy in the 21st
century and beyond."
-Hirofumi Tezuka, director and general manager
Kyocera Corporation, Solar Division
1.1 Introduction
We have only one planet that we can call home. Yet, we are slowly destroying this
home with every litre of fossil fuel that we burn every day. No option, you say?
Of course there's an option. The Sun. India is one of the sunniest countries in the
world, with 250 – 300 sunny days every year. And we let this wonderful bounty of
nature go to waste.
Due to recent developments in photovoltaic technology, one can easily convert
solar energy to electrical power and store it for use whenever we need it. Solar
energy is free, virtually inexhaustible and does not pollute the planet. Surprisingly,
it is also very economical in the long run.
As people are much concerned with the fossil fuel exhaustion and the
environmental problems caused by the conventional power generation, renewable
energy sources and among them photovoltaic panels and wind-generators are
widely used now.
The efficiency of a PV plant is affected mainly by three factors:
the efficiency of the PV panel (in commercial PV panels it is between 8-15% )
the efficiency of the inverter (95-98 % )
the efficiency of the MPPT algorithm (which is over 98% )
Improving the efficiency of the PV panel and the inverter is not easy as it depends
on the technology available, it may require better components, which can increase
drastically the cost of the installation. Instead, improving the tracking of the
maximum power point (MPP) with new control algorithms is easier, not expensive
and can be done even in plants which are already in use by updating their control
algorithms, which would lead to an immediate increase in PV power generation
and consequently a reduction in its price.
MPPT algorithms are necessary because PV arrays have a nonlinear voltage-
current characteristic with a unique point where the power produced is maximum.
This point depends on the temperature of the panels and on the irradiance
conditions. Both conditions change during the day and are also different depending
on the season of the year. Furthermore, irradiation can change rapidly due to
changing atmospheric conditions such as clouds. It is very important to track the
MPP accurately under all possible conditions so that the maximum available power
is always obtained.
In this project, the perturb and observe (P&O) and incremental conductance
(InCond) algorithms are analyzed in depth and tested according to the standard
conditions mentioned above. After that, improvements to the P&O and the InCond
algorithms are suggested to succeed in the MPP tracking under conditions of
changing irradiance.
To test the MPPT algorithms according to the irradiation profiles proposed in the
standard, a simplified model was developed, because the simulation time required
in some of the cases cannot be reached with the detailed switching model of a
power converter in a normal desktop computer. The reason for that is that the
computer runs out of memory after simulating only a few seconds with the
complete model. Finally, each method is evaluated and their strengths and
weakness are identified.
CHAPTER – 2
PV ARRAY MODELLING
2.1 PHOTOVOLTAIC MODULES
Solar cells consist of a p-n junction fabricated in a thin wafer or layer of
semiconductor. In the dark, the I-V output characteristic of a solar cell has an
exponential characteristic similar to that of a diode.
Fig 2.1 Basic Solar Cell Construction
When exposed to light, photons with energy greater than the band gap energy of
the semiconductor are absorbed and create an electron-hole pair. These carriers are
swept apart under the influence of the internal electric fields of the p-n junction
and create a current proportional to the incident radiation. When the cell is short
circuited, this current flows in the external circuit; when open circuited, this
current is shunted internally by the intrinsic p-n junction diode. The characteristics
of this diode therefore set the open circuit voltage characteristics of the cell.
2.2 Equivalent circuit of a solar cell
The solar cell can be represented by the electrical model shown in Figure.
Fig 2.2 Electrical model of Solar cell
Its current voltage characteristic is expressed by the following equation:
[ ( )
]
(1)
where I and V are the solar cell output current and voltage respectively, I0is the
dark saturation current, q is the charge of an electron, A is the diode quality
(ideality) factor, k is the Boltzmann constant, T is the absolute temperature and RS
and RSH are the series and shunt resistances of the solar cell. RS is the resistance
offered by the contacts and the bulk semiconductor material of the solar cell. The
origin of the shunt resistance RSH is more difficult to explain. It is related to the
non-ideal nature of the p–n junction and the presence of impurities near the edges
of the cell that provide a short-circuit path around the junction. In an ideal case RS
would be zero and RSH infinite. However, this ideal scenario is not possible and
manufacturers try to minimize the effect of both resistances to improve their
products. Sometimes, to simplify the model, the effect of the shunt resistance is not
considered, i.e. RSH is infinite, so the last term in the above equation is neglected.
A PV panel is composed of many solar cells, which are connected in series and
parallel so the output current and voltage of the PV panel are high enough to the
requirements of the grid or equipment. Taking into account the simplification
mentioned above, the output current-voltage characteristic of a PV panel is
expressed by an equation, where np and ns are the number of solar cells in parallel
and series respectively.
[ ( )
] (2)
2.3 Open circuit voltage, short circuit current and maximum power point
Two important points of the current-voltage characteristic must be pointed out: the
open circuit voltage VOC and the short circuit current ISC. At both points the power
generated is zero. VOC can be approximated from (1) when the output current of the
cell is zero, i.e. I=0 and the shunt resistance RSH is neglected. It is represented by
equation (3). The short circuit current ISC is the current at V = 0 and is
approximately equal to the light generated current IL as shown in equation (4).
(
) (3)
(4)
The maximum power is generated by the solar cell at a point of the current-voltage
characteristics, where the product VI is maximum. This point is known as the MPP
and is unique, as can be seen in Figure 2.3, where the previous points are
represented.
Fig 2.3 Characteristics of Solar Cell
2.4 Fill factor
Using the MPP current and voltage, IMPP and VMPP, the open circuit voltage (VOC)
and the short circuit current (ISC), the fill factor (FF) can be defined as:
(5)
It is a widely used measure of the solar cell overall quality.
It is the ratio of the actual maximum power (IMPPVMPP) to the theoretical one
(ISCVOC), which is actually not obtainable. The reason for that is that the MPP
voltage and current are always below the open circuit voltage and the short circuit
current respectively, because of the series and shunt resistances and the diode
depicted in Figure 2.2. The typical fill factor for commercial solar cells is usually
over 0.70.
2.5 Temperature and irradiance effects
Two important factors that have to be taken into account are the irradiation and the
temperature. They strongly affect the characteristics of solar modules. As a result,
the MPP varies during the day and that is the main reason why the MPP must
constantly be tracked and ensure that the maximum available power is obtained
from the panel.
The effect of the irradiance on the voltage-current (V-I) and voltage-power (V-P)
characteristics is depicted in Figure 2.4, where the curves are shown in per unit, i.e.
the voltage and current are normalized using the VOC and the ISC respectively, in
order to illustrate better the effects of the irradiance on the V-I and V-P curves. As
was previously mentioned, the photon-generated current is directly proportional to
the irradiance level, so an increment in the irradiation leads to a higher photo-
generated current. Moreover, the short circuit current is directly proportional to the
photon- generated current; therefore it is directly proportional to the irradiance.
Fig 2.4V-I and V-P curves at constant temperature (25°C) and three different insolation values.
When the operating point is not the short circuit, in which no power is generated,
the photon generated current is also the main factor in the PV current, as is
expressed by equations (1) and (2). For this reason the voltage-current
characteristic varies with the irradiation.
In contrast, the effect in the open circuit voltage is relatively small, as the
dependence of the light generated current is logarithmic, as is shown in equation
(3).
Figure 2.4 shows that the change in the current is greater than in the voltage. In
practice, the voltage dependency on the irradiation is often neglected . As the effect
on both the current and voltage is positive, i.e. both increase when the irradiation
rises, the effect on the power is also positive: the more irradiation, the more power
is generated.
The temperature, on the other hand, affects mostly the voltage. The open circuit
voltage is linearly dependent on the temperature, as shown in the following
equation:
( )
( ) (6)
According to (6), the effect of the temperature on VOC is negative, because Kv is
negative, i.e. when the temperature raises, the voltage decreases. The current
increases with the temperature but very little and it does not compensate the
decrease in the voltage caused by a given temperature rise. That is why the power
also decreases. PV panel manufacturers provide in their data sheets the temperature
coefficients, which are the parameters that specify how the open circuit voltage,
the short circuit current and the maximum power vary when the temperature
changes. As the effect of the temperature on the current is really small, it is usually
neglected.
Figure 2.5 shows how the voltage-current and the voltage-power characteristics
change with temperature. The curves are again in per unit, as in the previous case.
Fig 2.5V-I and V-P curves at constant irradiation (1 kW/m2) and three different temperatures.
As was mentioned before, the temperature and the irradiation depend on the
atmospheric conditions, which are not constant during the year and not even during
a single day; they can vary rapidly due to fast changing conditions such as clouds.
This causes the MPP to move continuously, depending on the irradiation and
temperature conditions. If the operating point is not close to the MPP, great power
losses occur.
Hence it is essential to track the MPP in any conditions to assure that the
maximum available power is obtained from the PV panel. In a modern solar power
converter, this task is entrusted to the MPPT algorithms.
CHAPTER – 3
SOLAR CHARGE CONTROLLER
3.1 MPPT based Solar Charge Controller:
A maximum power point tracker (or MPPT) based Solar Charge Controller is a
high efficiency DC to DC converter which functions as an optimal electrical load
for a photovoltaic (PV) cell, most commonly for a solar panel or array, and
converts the power to a voltage or current level which is more suitable to whatever
load the system is designed to drive.
Fig 3.1 Schematic representation of MPPT charge Controller
Typically a charge controller performs the following basic functions:
Controls maximum power extraction from a panel by tracking the MPP and
ensuring that the panel operates at MPP.
Controls battery charging as defined in the battery charge cycle
specification to improve usable battery life and protect it against reverse
connection, over charging and deep discharging
Load protection against overloads and short-circuits
Display (LED or LCD) Status indications
3.2 Converter Choice for MPPT
Depending on the topology of the power electronics, an MPPT charge controller
cans be either:
• Buck only – the PV voltage must be higher than the battery voltage
• Boost only – the PV voltage must be lower than battery voltage
• Buck-boost – both the PV voltage and battery voltage can be variable values
with the system switching between buck and boost based on the relative voltages.
Fig 3.1 shows the block diagram of a MPPT Charge Controller
3.3 Boost Converter
The maximum power point tracking is basically a load matching problem. In order
to change the input resistance of the panel to match the load resistance (by varying
the duty cycle), a DC to DC converter is required.
It has been studied that the efficiency of the DC to DC converter is maximum for a
buck converter, then for a buck-boost converter and minimum for a boost converter
but as we intend to use our system either for tying to a grid or for a system which
requires 230 Vat the output end, so we use a boost converter. Fig 3.2 shows the
circuit diagram of Boost Converter.
Fig 3.2 Circuit diagram of Boost Converter
3.3.1 Mode 1 operation of the Boost Converter
When the switch is closed the inductor gets energized through the battery and
stores the energy. In this mode inductor current rises (exponentially) but for
simplicity we assume that the energizing and the de - energizing of the inductor are
linear. The diode blocks the current flowing and so the load current remains
constant which is being supplied due to the discharging of the capacitor. Fig 3.3
shows the Mode 1 Operation of Boost Converter.
Fig 3.3 Mode 1 Operation of Boost Converter
3.3.2 Mode 2 operation of the Boost Converter
In mode 2 the switch is open and so the diode becomes short circuited. The energy
stored in the inductor gets utilized through opposite polarities which charge the
capacitor. The load current remains constant throughout the operation. Fig 3.4
shows the Mode 1 Operation of Boost Converter.
The waveforms for a boost converter are shown in Figure 3.5
Fig 3.4 Mode 2 Operation of Boost Converter
Fig 3.5 Waveforms for a Boost Converter
CHAPTER - 4
MAXIMUM POWER POINT TRACKING ALGORITHMS
4.1 An overview of Maximum Power Point Tracking
The power output from the solar panel is a function of insolation level and
temperature. But for a given operating condition, we have a curve which gives the
voltage level maintained by the panel for a particular value of current. This plot is
known as the characteristics of the cell. From the characteristics plot, we will be
able to derive the power output with respect to the output current. We adopt the
method to find the current which has to be extracted so as to fix the operating point
of the cell at its maximum power.
Fig 4.1 PV Panel Characteristic curves
The operating point of any source sink mechanism is the intersection point of load
line with the source characteristic plot shown in fig 4.1. What we attempt here to
do is change the load angle theta (𝜃) to intersect the characteristics at maximum
power point i.e., nothing but the solution for impedance matching problem. The
principle is described below.
PV modules have a very low conversion efficiency of around 15% for the
manufactured ones. Besides, due to the temperature, radiation and load variations,
this efficiency can be highly reduced.
In fact, the efficiency of any semiconductor device drops steeply with the
temperature. In order to ensure that the photovoltaic modules always act supplying
the maximum power as possible and dictated by ambient operating conditions, a
specific circuit known as MPPT is employed.
In most common applications, the MPPT is a DC-DC converter controlled through
a strategy that allows imposing the photovoltaic module operation point on the
Maximum Power Point (MPP) or close to it. On the literature, many studies
describing techniques to improve MPP algorithms were published, permitting more
velocity and precision of tracking.
On the other hand, there is no theory to guide the designer to choose, among the
DC-DC converters family, the best one to operate as MPPT, thus, in most cases,
the designers are tempted to use the simplest DC-DC converters – namely buck
converter or boost converter.
4.2 Different MPPT techniques
There are different techniques used to track the maximum power point. Two of the
most popular techniques are:
Perturb & Observe Method
Incremental Conductance Method
The choice of the algorithm depends on the time complexity the algorithm takes to
track the MPP, implementation cost and the ease of implementation.
4.2.1 Perturb & Observe
Perturb & Observe (P&O) is the simplest method. Fig 4.2 shows the algorithmic
flowchart of Perturb & Observe method for MPPT. In this we use only one sensor,
that is the voltage sensor, to sense the PV array voltage and so the cost of
implementation is less and hence easy to implement. The time complexity of this
algorithm is very less but on reaching very close to the MPP it doesn’t stop at the
MPP and keeps on perturbing on both the directions. Fig 4.3 shows the Illustration
of MPPT Algorithm When this happens the algorithm has reached very close to the
MPP and we can set an appropriate error limit or can use a wait function which
ends up increasing the time complexity of the algorithm. However the method does
not take account of the rapid change of irradiation level (due to which MPPT
changes) and considers it as a change in MPP due to perturbation and ends up
calculating the wrong MPP. To avoid this problem we can use incremental
conductance method. The Perturb & Observe algorithm states that when the
operating voltage of the PV panel is perturbed by a small increment, if the resulting
changes in power ΔP is positive, then we are going in the direction of MPP and we
keep on perturbing in the same direction. If ΔP is negative, we are going away
from the direction of MPP and the sign of perturbation supplied has to be changed.
Fig 4.3 Illustration of P&O MPPT Algorithm
The flowchart for the P&O algorithm is shown in Figure 4.2
Fig 4.2 Algorithmic flow chart of Perturb & Observe method for MPPT
Start
Measure V(k)& I(k)
P(k)= V(k)* I(k)
ΔP = P(k)-P(k-1)
ΔP > 0
Decrease Array
Voltage
V(k) – V(k-1) > 0 V(k) – V(k-1) > 0
Increase Array
voltage
Update history
V(k-1)= V(k)
P(k-1)= P(k)
Decrease Array Voltage
Increase Array voltage
NO YES
YES YESNO NO
Figure 4.1 shows the plot of module output power versus module voltage for a
solar panel at a given irradiation. The point marked as MPP is the Maximum
Power Point, the theoretical maximum output obtainable from the PV panel.
Consider A and B as two operating points as shown in the figure above, the point
A is on the left hand side of the MPP. Therefore, we can move towards the MPP by
providing a positive perturbation to the voltage.
On the other hand, point B is on the right hand side of the MPP. When we give a
positive perturbation, the value of ΔP becomes negative, thus it is imperative to
change the direction of perturbation to achieve MPP.
4.2.2. Incremental Conductance Method
The theory of the incremental conductance method is to determine the variation
direction of the terminal voltage for PV modules by measuring and comparing the
incremental conductance and instantaneous conductance of PV modules. If the
value of incremental conductance is equal to that of instantaneous conductance, it
represents that the maximum power point is found.
The basic theory is illustrated with Fig. 4.4.
Fig 4.4 Illustration of InCond MPPT Algorithm
When the operating behavior of PV modules is within the constant current area,
the output power is proportional to the terminal voltage. That means the output
power increases linearly with the increasing terminal voltage of PV modules
(slope of the power curve is positive, dP/dV> 0). When the operating point of
PV modules passes through the maximum power point, its operating behavior is
similar to constant voltage. Therefore, the output power decreases linearly with the
increasing terminal voltage of PV modules (slope of the power curve is negative,
dP/dV< 0). When the operating point of PV modules is exactly on the maximum
power point, the slope of the power curve is zero (dP/dV= 0) and can be further
expressed as,
( )
( )
By the relationship of dP/dV= 0, (7) can be rearranged as follows,
( )
dI and dV represent the current error and voltage error before and after the
increment respectively. The static conductance (Gs) and the dynamic conductance
(Gd, incremental conductance) of PV modules are defined as follows,
( )
( )
The maximum power point (operating voltage is Vm) can be found When
(11)
When the equation in (8) comes in to existence, the maximum power point is
tracked by MPPT system. However, the following situations will happen while the
operating point is not on the maximum power point:
(
) ( )
(
) ( )
Equations (12) and (13) are used to determine the direction of voltage perturbation
when the operating point moves toward to the maximum power point.
In the process of tracking, the terminal voltage of PV modules will continuously
perturb until the condition of (8) comes into existence.
The main difference between incremental conductance and P&O algorithms is the
judgment on determining the direction of voltage perturbation. When static
conductance Gs is equal to dynamic conductance Gd, the maximum power point
is found.
From the flow diagram shown in Fig.4.5, it can be observed that the weather
conditions don’t change and the operating point is located on the maximum power
point when dV= 0 and dI= 0. If dV= 0 but dI> 0, it represents that the sun
irradiance increases and the voltage of the maximum power point rises.
Meanwhile, the maximum power point tracker has to raise the operating voltage of
PV modules in order to track the maximum power point.
On the contrary, the sun irradiance decreases and the voltage of the maximum
power point reduces if dI< 0. At this time the maximum power point tracker needs
to reduce the operating voltage of PV modules.
Furthermore, when the voltage and current of PV modules change during a
voltage perturbation and dI/dV>-I/V (dP/dV> 0), the operating voltage of PV
modules are located on the left side of the maximum power point in the P-V
diagram, and have to be raised in order to track the maximum power point.
If dI/dV<-I/V(dP/dV< 0), the operating voltage of PV modules will be located on
the right side of the maximum power point in the P-V diagram, and has to be
reduced in order to track the maximum power point. The advantage of the
incremental conductance method, which is superior to those of the other two
MPPT algorithms, is that it can calculate and find the exact perturbation direction
for the operating voltage of PV modules. In theory, when the maximum power
point is found by the judgment conditions (dI/dV= -I/V and dI= 0) of the
incremental conductance method, it can avoid the perturbation phenomenon near
the maximum power point which is usually happened for the other two MPPT
algorithms. The value of operating voltage is then fixed. However, it indicates that
perturbation phenomenon is still happened near the maximum power point under
stable weather conditions after doing some experiments. This is due to the reason
that the probability of meeting condition dI/dV=-I/V is extremely small.
Fig.4.5 Algorithmic flowchart of Incremental Conductance method for MPPT
Inputs: V(t),I(t),V(t-Δt),I(t-Δt)
P(t),P(t-Δt) calculated from the inputs
ΔV = V(t) –V(t-Δt) ΔP = P(t) – P(t -Δt)
ΔI = I(t) – I(t - Δt)
ΔV/ΔP = 0
ΔI/ΔP = 0
ΔV/ΔP >0
ΔI/ΔP < 0
Increase Vref
Decrease Vref
Return
NO
NO
YES
YES
Summarily, the incremental conductance algorithm is based on the fact that the
slope of the curve power vs. voltage (current) of the PV module is zero at the MPP,
positive (negative) on the left of it and negative (positive) on the right, as can be
seen in Figure 4.5:
ΔV/ΔP = 0 (ΔI /ΔP = 0) at the MPP
ΔV/ΔP > 0 (ΔI /ΔP < 0) on the left
ΔV/ ΔP < 0 (ΔI / ΔP > 0) on the right
By comparing the increment of the power vs. the increment of the voltage (current)
between two consecutives samples, the change in the MPP voltage can be
determined.
CHAPTER – 5
SIMULATION & EVALUATION
5.1PSIM:
PSIM is a simulation package specifically designed for power electronics and
motor control. With fast simulation, friendly user interface and waveform
processing, PSIM provides a powerful simulation environment for power converter
analysis, control loop design, and motor drive system studies.
The PSIM simulation package consists of three programs: circuit schematic editor
SIMCAD*, PSIM simulator, and waveform processing program SIMVIEW*. The
simulation environment is illustrated as follows.
5.2 Circuit Structure
A circuit is represented in PSIM in four blocks: power circuit, control circuit,
sensors, and switch controllers. The figure below shows the relationship between
these blocks.
The power circuit consists of switching devices, RLC branches, transformers, and
coupled inductors. The control circuit is represented in block diagram.
Components in s domain and z domain, logic components (such as logic gates and
flip flops), and nonlinear components (such as multipliers and dividers) can be
used in the control circuit. Sensors measure power circuit voltages and currents and
pass the values to the control circuit. Gating signals are then generated from the
control circuit and sent back to the power circuit through switch controllers to
control switches.
5.3 SOLAR CELL MODELS
Two types of solar cells models are provided. One is the functional model that
requires the minimum parameter inputs, and the other is the physical model that
can take into account the light intensity and ambient temperature variations.
Fig 5.1 Physical Model of Solar Cell
Fig 5.2 Characteristics of Solar cell (Physical Model)
Fig 5.3 Functional Model of Solar Cell
Fig 5.4 Characteristics of Solar Cell (Functional model)
5.4 Simulation Model of Perturb & Observe Algorithm for MPPT:
Fig.5.5 Simulation Model of Perturb & Observe Algorithm for MPPT
Fig 5.6 Sub circuit model of P&O MPPT
Simulation Output:
Fig 5.7 Simulation output of P&O MPPT Algorithm
5.5 Limitations of Perturb & Observe algorithm
Fig 5.8 Curve showing wrong tracking of MPP by P&O algorithm under rapidly varying
irradiance
In a situation where the irradiance changes rapidly, the MPP also moves on the
right hand side of the curve. The algorithm takes it as a change due to perturbation
and in the next iteration it changes the direction of perturbation and hence goes
away from the MPP as shown in the figure.
However, in this algorithm we use only one sensor, that is the voltage sensor, to
sense the PV array voltage and so the cost of implementation is less and hence easy
to implement. The time complexity of this algorithm is very less but on reaching
very close to the MPP it doesn’t stop at the MPP and keeps on perturbing in both
the directions. When this happens the algorithm has reached very close to the MPP
and we can set an appropriate error limit or can use a wait function which ends up
increasing the time complexity of the algorithm.
5.6 Simulation Model of Incremental Conductance Method for MPPT:
Fig 5.9Simulation Model Incremental Conductance MPPT Algorithm
Simulation Output:
Fig 5.10 Simulation Output of Incremental Conductance MPPT Algorithm
5.7 Analysis and discussion of Simulation results:
In order to compare the accuracy and efficiency of the two MPPT algorithms
selected in this project, PSIM Software package is used to implement the tasks of
modeling and simulation. The PV module used in the PV system is the product of
Solarex whose model is MX64. This kind of PV module is composed of 72 solar
cells in series, and the electrical specification tested by the factory under
1000W/m2, AM1.5 and 25oC conditions is listed in Table 1.
Fig. 5.11 is the block diagram of the PV simulation system used in this paper. The
hardware specification of the computer used for simulation is Intel Core i3
Processor M 370 @ 2.40GHz.
DC to DCConverter
MPPTController
Load
Ipv
Vpv
VpvIpv
Vout
pulses
Photovoltaic
Fig 5.11 Block diagram of PV Simulation system
Table 1: PV Panel Specifications
Power output Curve for P&O MPPT Algorithm:
Fig 5.12 MPPT Power output of Perturb and Observe Method
Power output Curve for Incremental Conductance MPPT Algorithm:
Fig 5.13 MPPT Power output of Incremental conductance MPPT Algorithm
The time response, the average power and the ripples amplitude of the output
power corresponding to the two treated MPPT controlled methods has been
obtained from the output graphs (above) and its comparison details are given
below table
And moreover, from the data points of the MPPT Power output curve, the
efficiency of an individual algorithm is determined.
The efficiency of two different methods under two different weather conditions are
determined and summarized in the table below.
Time
Response Average Power
Ripples
Amplitude
Perturb & Observe Method 4.08ms 53 watt 12 watt
Incremental Conductance
Method 4.37ms 59.52 watt 1.6 watt
Table 2: Comparison results
Weather P&O IncCond
Full sun 91.4% 94.6%
Partial Cloudy 95.6% 94.9%
Table 3: Comparison of efficiency
In general, the advantages of the ‘incremental conductance’ method over the
‘perturb and observe’ method are:
• Incremental method can calculate the direction, for which the array’s point
changed in order to reach the MPP,
• Incremental method should not oscillate about the MPP once it reaches it,
• Incremental method does not go on the wrong direction when conditions in the
system changed rapidly.
5.8 Conclusion
The sun is at the origin of the quasi-totality of the sources of energies used by the
humanity for its food, domestic and industrial needs. The solar energy is important
because it is non-pollutant energy. In this project, the conversion from solar energy
to electrical one is treated. In this case, the model of a photocell and a solar panel
are presented. The ‘Perturb and observe’ and the ‘incremental conductance’
methods are used to maximize the output power. The flow chart of each method
had been explained and discussed. With the incremental conductance method,
compared to the perturb and observe method, simulation results underline that the
time response is small, the existing ripples have low amplitude and the average
power is more important.