review on enhancement of stand alone hybrid power … · under conditions of changing irradiance...
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REVIEW ON ENHANCEMENT OF STAND ALONE HYBRID
POWER PLANT SYSTEM USING DIFFERENT MPPT
TECHNIQUES
1N.Subha Lakshmi,
2 Dr.S.Allirani,
3Dr.R.Sumathi,
4S.Sarumathi
1Assistant professor, Department of EEE, Sri Krishna College of Engineering & Technology, Coimbatore.
2Associate Professor, Department of EEE, Sri Ramakrishna Engineering College,Coimbatore.
3Associate Professor, Department of EEE, Sri Krishna College of Engineering & Technology, Coimbatore.
4Assistant professor, Department of EEE, Sri Krishna College of Engineering & Technology, Coimbatore.
Abstract
The solar cell arrays provide energy in the steady-state and the battery provides energy
in transient states. Here,a charge controller system based on the MPP trracking
technology, suitable for using in the islanded microgrid that contains a solar panel and a
battery is designed.The charge controller includes a unidirectional DC-DC converter as
an interface circuit between the battery and the DC bus with a control system and power
management in different states of irradiance and state of charge(SOC).A 200-W
prototype system is designed to construct and simulated in MATLAB/simulink software
. The simulation and experimental results are showing better performance of the
proposed charge controller.
In this paper attempt have been made to study and analyze different MPPT techniques
used in different scenarios to make it simple to choose a particular methodology for
particular situation. Variable step size maximum power point trackers (MPPTs) are widely
used in photovoltaic (PV) systems to extract the peak array power which depends on solar
irradiation and array temperature .The imperative factor which evaluates system transient
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and steady state performances is the scaling factor (N),which is used to update the
controlling equation in the tracing algorithm and to determine a new duty cycle.
Therefore, by using linear control theory, the boundary value of the scaling factor can be
determined . The theoretical investigations and the design fundamental of the proposed
stability analysis have been validated using MATLAB simulations.
1. INTRODUCTION
The world energy scenario is changing abruptly . The huge power demand the world face is
becoming a challenge to human day by day. Technology improvements have helped to face this
situation better , But it also have created other more challenges regarding the quality of power
and efficiency . The conventional energy sources that we relied upon are in stage of being
replaced by the renewable energy sources that are widely available. Recent researches focus
mainly on the solar energy . Many studies have made it possible to convert these energies into
more efficient electrical energy. The intervention of power electronics in almost of all the fields
have made more sophistication in industries with loads that require the most efficient and
accurate amount of supply . The terminology Maximum power point tracking came into
existence with all these conditions . MPPT is a method to obtain the maximum power from a
module in any weather condition . As solar energy is varying in nature , the MPPT is the main
focus of energy conservation.
The objective of this paper is to review different MPPT algorithms namely Perturb and
observe (P&O), incremental conductance (InCond) and fuzzy logic control (FLC) are analysed.
The improvements to the P&O algorithm are suggested to incorporate 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 and simulated
using MATLAB.
2. REVIEWS ON MPPT
Many algorithms are formulated for PV system. The main aim is to find the point in the V-I
characteristics of the solar panel, at which the product of voltage and current is maximum. It is
found that there is only one point in the curve at particular temperature and irradiation condition.
Fig 1(a) shows voltage vs current characteristics of a solar cell at variable environmental
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conditions. For varying temperature the power value also varies, which is shown in Fig 1(b).For
increase in irradiance the power is also increased.
Fig: 1.(a) V-I characteristics (b) P-V characteristics of PV panel
A. Perturb and observe method:
This is the basic hill climbing algorithm used. First the PV voltage and current are measured
and the corresponding power is calculated. The present and previously obtained power values are
then compared . If power calculate after perturbation is more than first, then the perturbation is in
the correct direction; otherwise it should be reversed. In this way , the peak power point is
recognized and hence the corresponding voltage can be calculated. P&O/hill-climbing show
occasional deviation from the maximum operating point in case of rapidly changing atmospheric
conditions. The perturbation size is important in providing good performance in both dynamic
and steady-state response . To achieve better result an adaptive hill climbing technique, with a
variable perturbation step size can be formulated, where an automatic tuning controller varies the
perturbation step size according to the environmental condition.
Fig.2 Schematic representation of adaptive perturb and observe method
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In the Adaptive P&O method, instead of Vmpp the main emphasis has been given on the
voltage perturbation . Fig.2 is the schematic representation of Adaptive Perturb and observe
method . A constant duty cycle perturbation that shows linear-inverse response to power drawn
from PV panel has been taken in predictive and adaptive MPPT P&O method.
2.1 Incremental conductance method:
For a PV system, the derivative of panel output power with its voltage is expressed
as
(1.1) Certain conditions can be considered to track the direction of MPP
at MPP (1.2)
at left of MPP (1.3)
at right of MPP (1.4) MPP can be tracked by comparing the instantaneous (I/V) conductance to the incremental
conductance (∆I/∆V).This algorithm is similar to Perturb and observe method which require step
size to observe proper perturbation size. But it requires complex and costly control circuits.
3. EXISTING SYSTEM
In this method the peak power of the module lies at above 98% of its incremental
conductance. The flow chart of incremental conductance MPPT is shown below.
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Fig 3. Incremental conductance MPPT Flow chart
Fig.4 Block diagram for existing system
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MPPT or Maximum Power Point Tracking is algorithm which is used in charge controllers
for taking maximum power available from Photo Voltaic module under certain conditions. The
voltage at which PV module can make maximum power production is called “maximum power
point” (or peak power voltage).Maximum power production differs with solar radiation, ambient
temperature and temperature of solar cell. MPPT checks output of PV module, relate it to battery
voltage then finalise with the best power that PV module can produce to charge the battery and
converts inturn gives the maximum current into battery. It can also supply power to a DC load,
which is directly connected to the battery. MPPT algorithm can be best suitable for both buck and
boost power converter depending on system design. Normally, for battery system voltage is equal
or less than 48 V, buck converter plays a role. On the other hand, if battery system voltage is
greater than 48 V, boost converter is suitable for application. In incremental conductance method
the array terminal voltage is always adjusted according to the MPPT voltage which is based on
the incremental and instantaneous conductance of the PV module..
4. PROPOSED SYSYTEM
In this method, a control tracking algorithm is developed to follow the MPP of the PV
field that is the MPPT algorithm. P&O method algorithm is used for perturbation in the operating
voltage of the PV array in a system. Perturbing this duty ratio of power converter results in
perturbation of the PV array current which in turn perturbs the PV array voltage. It can be infered
that if power is increased or decreased then the voltage is incremented or decremented
accordingly and the operating point rely on the left of the MPP. When the power decreases or
increases for the increase of voltage then the operating point rely on the right of the MPP. Hence,
it is shown that if power increase, the succeeding perturbation should be kept the same to reach
the MPP and in the case of power decrease, the perturbation should be vice versa.
The procedure is repeated in regular manner until the MPP is reached. The system is
then made to oscillate until the MPP is reached. Reducing the perturbation step size, makes the
oscillation to be minimized. However, a lesser pertubation size slows down the MPPT. A
solution to this contradictory situation is to have a changeble perturbation size that gets lower
towards the MPP. The P& O method not able to track the MPP when the irradiance
changes quickly; and it fluctuation has been taken on repeated perturb and observe method to
improve its occurrence.
.
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5. SIMULATION RESULTS AND DISCUSSION
The Fig 5 is the simulation block of the proposed system. The currents and voltage output
from the PV Panel is given to the P&O controller to generate variable duty cycle . This duty cycle
is given as the input to the boost converter for proper switching sequence. For simplicity, the
output of system is observed across a load resistance. The powergui block is set as discrete since
the control strategy used is discrete.
Fig 5 Simulation of PV system with P&O MPPT controller .
Fig 6. System output
5.1 SYSTEM PARAMETERS
The system is designed considering certain standard values and random choice of
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parameter value. The single diode circuit is considered at normal irradiance condition.
Parameter values
Number of cells in series (Ns) : 10
Number of cells in parallel (Np) : 6
Open circuit voltage (Voc) : 37.51 V
Short circuit current (Isc) : 8.63 A
Inductor(L) : 1 Mh
Capacitor(C1,C2) : 47 F
Resistor(Rload) : 30
Gain value : 0.038
Switching frequency : 30 KHZ
Sampling time(Ts) : 0.01s
These parameters are used to design the converter small signal model. The converter transfer
function is calculated and designed to obtain the boosted output.
5.2 PV SUBSYSTEM
The PV module as in Fig 7 is designed using Matlab coding and equivalent solar cell circuit.
MATLAB code is generated to produce current output.
Fig 7 Simulation diagram of PV system
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Fig 8 Output waveform of simulation of PV subsystem
5.3 DC-DC CONVERTER SUBSYSTEM
The converter circuit is modeled with help of MOSFET switch. The voltage output
from the PV module is given as input to the converter. The duty cycle is generated from
the P&O control block. The parameter values for the converter are chosen from a
conventional system [11]. The output voltage is boosted up to 78.11V.
Fig 9 Simulation diagram of DC-DC converter
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The output obtained is:
PV voltage output (Vout) : 41.7V
Converter voltage output (Vout) : 78.1 V
Maximum Current (Impp) : 4.47 A
Error Gain(g) : 0.27
Power Maximum (Pmpp) : 340.08 W
Fig 10 Boost converter output
5.4 SYSTEM OUTPUT AND INTERFERENCE
The voltage and power values are noted from workspace to obtain the PV curve of the
system with maximum power output. From fig 6.2 it is clear that the PV curve obtained denotes
a unique maximum power point. But it has many transients and needs to be tuned more by
varying the scaling factor and duty cycle. The PV curve obtained denoted the efficiency of the
discrete control block. The curve does not follow a smooth transient. Thus the chosen parameters
need to be varied according to system design and analysis is to be done. The transfer function of
the small signal model is to be designed more accurately to obtain clearer curve.The error
linearization control loop should be coupled with P&O control block to reduce the transients in
the power curve and to track the maximum power point at varying irradiance condition.
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6. REFERENCES
[1] Yuncong Jiang Jaber A.Abu Qahouq and Tim A.Haskew,”Adaptive Step Size
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2013
[2] Mhamed Rebhi,Al Bentillah,Mubrouk Sellam and Boufeldja Kadri,”Compartive
Study ofMPPT Controllers for PV System Implemented in the South-west of
Algeria,”Energy Procedia 36 (2013) 142-153
[3] Christos Konstantopoulos and Eftichios Koutrouliss,”Global Maximum Power Point
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[7] R.Ramaprabha, B.L. Mathur,”Intelligent Controller based Maximum Power Point
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[8] Prof.Seppo Ovaska,D.Sc. (Tech) Konstantin Kostav “Maximum Power Point Tracking
Algorithms for Photovoltaic Applications,”Abstract of the master’s thesis,Aolto university
school of science and technology December 2010
[9] Qiang Mei,Mingwei Shan,Liying Liu and Joseph M.Guerrero,”A Novel
Improved Variable Step-Size Incremental-Resistance MPPT Method for PV
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