Output Voltage Sensor based Maximum Power
Point Tracking for PV system using SEPIC
Muralidhar Killi
Susovon Samanta
Department of Electrical Engineering
National Institute of Technology
Rourkela, India 769008
Email: [email protected]
Department of Electrical Engineering
National Institute of Technology
Rourkela, India 769008
Email: [email protected]
Telephone: 0661–2462420
Abstract—Maximum power point tracking (MPPT) algorithm
with a single output voltage sensor for a photovoltaic (PV) system
is presented in this paper. The MPPT algorithm is developed
o
) of Vo − D characteristics. In
by considering the slope ( dV
dD
this method only a voltage divider circuit is used to sense the
converter output voltage (Vo ). The steady state behavior, tracking
performance for a change in insolation and for a load variation
with the output voltage sensor based MPPT algorithm are
addressed through experimental results to determine the tracking
efficiency. The duty cycle (D) is generated directly without any
proportional-integral control loop to simplify the control circuit.
Single ended primary inductance converter (SEPIC) is used for
experimental validation of the algorithm with microcontroller.
Index Terms—Photovoltaic (PV), voltage sensor, maximum
power point tracking (MPPT), and single ended primary inductance converter (SEPIC).
I. I NTRODUCTION
The increased energy demand and shortage of fossil reserves
motivated researchers to focus on renewable energy sources.
Among the existing renewable energy sources photovoltaic
power generation is evolving as one of the most remarkable
renewable energy source because of its benefits such as ecofriendly nature, less maintenance and no noise. The I − V
characteristics of a PV module will vary with solar insolation and atmospheric temperature [1], [2]. Efficiency of the
PV system primarily depends on the operating point on the
characteristic curve of the PV module. Maximum power point
(MPP) exists for a PV module where the output power from
the module is maximum. So far a large number of maximum
power point tracking (MPPT) techniques have been developed
[3]–[18] to increase the efficiency of the PV system.
MPPT algorithms can be classified mainly into two categories one is input parameter based and another is output
parameter based. MPPT algorithms such as fractional open
circuit voltage [3], fractional short circuit current [4], Hillclimbing [5], perturb and observe (P&O) [6]–[8], incremental
conductance (IncCond) [9], [10], incremental resistance (INR)
[11], ripple correlation control (RCC) [12], techniques have
been developed to extract the maximum power from the PV
arrays by using the input parameter/s either VP V (PV module
voltage) or IP V (PV module current) or both. Among the
various MPPT techniques, fractional open circuit voltage and
short circuit current techniques provide a simple and effective
way to extract maximum power, but they require periodical
measurement of open circuit voltage or short circuit current
for reference, causing more power loss. From the literature it
is observed that P&O and IncCond methods are extensively
applied methods because of their increased efficiency and
ease of implementation [13]. However with the P&O-like
algorithms the operating point moves away from MPP while
there is a rapid increase in insolation [6]–[9]. The RCC MPPT
algorithm requires the time derivative of the power converter
voltage and current ripples to determine the position of the
operating point on the characteristic curve of the PV module.
So for high frequency converter it is very difficult to obtain
the accurate time derivative of the array voltage and current.
Other existing techniques show improved performance using
fuzzy logic, neural network, optimization algorithm, sliding
mode control, but they are not commonly used due to their
complexity and need of expensive digital processor. Overview
of all the MPPT techniques published recently are thoroughly
discussed in [13]–[15].
The MPPT algorithm can also be implemented by using
output parameters such as either Vo (converter output voltage)
or Io (converter output current) depending on the type of load
[16]–[18]. In [16] it is discussed that for a battery load,
the available maximum power can be extracted from the PV
module by maximising only the battery current and in [17]
the MPPT method is developed by sensing the output current
for a battery load. The possibility of using output parameter
i.e., either voltage or current to track the MPP is depends on
the type of load and the corresponding analysis is presented
in [18]. However in [17], [18] the tracking performance for a
change of insolation and steady state behaviour of the MPPT
algorithm are not demonstrated.
This paper presents a clear illustration behind the usage of
output parameters rather than input parameters for tracking
the MPP by using Vo − D and Io − D characteristics. Most
of the practical PV systems contains battery, where the output
voltage and current are to be measured for the purpose of
charge control and battery protection. By using only the output
parameters, both objectives of MPPT and charge control of
battery can be achieved which results in reduction of cost of
the PV system. Moreover this MPPT algorithm is efficient,
simple and robust to load variations. The tracking perfor-
mance and steady state behaviour of the MPPT algorithm
are clearly demonstrated through experimental results. In this
paper SEPIC converter is considered because SEPIC works as
step-up/step-down converter [19], [20], thereby it will increase
the range of operation of PV voltage. This topology has merits
of non-inverting output polarity, easy to drive switch and low
input current ripple.
This paper is organized as follows: Output voltage sensor
based MPPT algorithm and it’s steady state 3-level operation
are presented in Section II. Experimental results are given in
Section III and Finally conclusions are presented in Section
IV.
For clear understanding of the working principle of the
output voltage sensor based MPPT algorithm, the waveforms
of output voltage (Vo ), current (Io ) and power (Po ) are
captured by increasing the duty cycle from 0.1 to 0.9 and
are shown in Fig. 3. From Fig. 3 it can be visualised that the
maximum output power from the converter connected with
PV source can be achieved at a particular duty cycle where
dVo
dD = 0. Thus MPPT algorithm can be implemented using a
o
single output voltage sensor by evaluating dV
dD without any
input parameters for a resistive load. For battery load the
output current has to sensed to implement the MPPT algorithm
[18].
II. O UTPUT VOLTAGE SENSOR BASED MPPT
MPPT controller is aiming to extract the available maximum
power from the PV module or array irrespective of the
insolation (G) and temperature (T ) variations. If the load
is directly connected to the PV module it is not possible
to operate at peak power point due to impedance mismatch.
Converter facilitates to transfer maximum power from the PV
module to the load by changing the duty cycle generated by
the MPPT controller and a general block diagram of the PV
system with MPPT controller is shown in Fig. 1.
(a)
Figure 1. Block digram of PV system with MPPT control.
The output voltage sensor based MPPT algorithm is developed based on Vo − D characteristics. Where Vo is converter
output voltage and D is duty cycle of the converter. The
PV module voltage (VP V ) and converter output voltage (Vo )
waveforms are captured by increasing the duty cycle from 0.1
to 0.9 and are shown in Fig. 2. From the Vo −D characteristics
o
shown in Fig. 2, it can be observed that the slope ( dV
dD ) varies
depending on the position of the operating point and is given
by (1)

= 0, at MPP
dVo 
> 0, on left of MPP
(1)
dD 
< 0, on right of MPP
(b)
Figure 2. Variation of VP V and Vo with respect to duty cycle (a) for an
insolation of G = 270W/m2 and (b) for an insolation of G = 480W/m2 .
Moreover maximum value of Vo and VMP P (PV module
voltage at MPP) are occurring at same duty cycle and it can
be seen form Fig. 2. Thus the maximum power from the PV
o
module can be tracked by evaluating dV
dD by sensing only the
output voltage [17], [18]. The duty cycle has to be incremented
or decremented by ∆D (perturbation step size) depending on
o
the sign of dV
dD as given by (2)
D (k + 1 ) = D (k ) ± ∆D
(2)
(a)
the generated PWM control signal is given to the SEPIC
converter. The circuit model of the designed PV system and the
experimental setup are shown in Fig. 4 and Fig. 5 respectively.
(b)
Figure 3. Variation of Vo , Io and Po with respect to duty cycle (a) for an
insolation of G = 270W/m2 and (b) for an insolation of G = 480W/m2 .
Figure 4. Circuit Model of Developed PV system.
The pseudo code for the proposed algorithm is given below.
Initialize Vo (k − 1) at D(k − 1)
Loop: Sample and average Vo (k)
o
Calculate dV
dD
dVo
If( dD > 0)
D(k + 1) = D(k) + ∆D
OR
o
If( dV
dD < 0)
D(k + 1) = D(k) - ∆D
ELSE
No Change
D(k + 1) = D(k)
GOTO Loop
Figure 5. Experimental setup of Developed PV system.
A. Steady state behaviour of the MPPT algorithm
Three level operation of the output voltage sensor based
MPPT algorithm in steady state is depicted in Fig. 2(a).
Assume that the operating point has been moved from point
1 to point 2 and decision has to be taken at point 2 by
considering the values of dVo and dD. As dVo = (Vo2 −Vo1 ) >
0 and dD = (D2 − D1 ) > 0, the algorithm increases
the duty cycle and hence the operating point moves to the
3 At point 3 as dVo = (Vo3 − Vo2 ) < 0 and
point .
dD = (D3 − D2 ) > 0 the algorithm decreases the duty cycle
2 At
and thereby the operating point moves back to point .
2 as dVo = (Vo2 − Vo3 ) > 0 and dD = (D2 − D3 ) < 0
point the algorithm decreases the duty cycle and hence the operating
1 At point 1 as dVo = (Vo1 −Vo2 ) < 0
point moves to point .
and dD = (D1 − D2 ) < 0 the algorithm increases the duty
cycle and thereby the operating point moves back to point
2 In this pattern the algorithm makes the operating point to
.
oscillate in three points surrounding the MPP.
(a)
III. EXPERIMENTAL VALIDATION
To validate the functionality and tracking performance of the
output voltage sensor based MPPT algorithm, a prototype of
SEPIC converter is developed with the designed parameters
presented in Table. 1. ARDUINO ATMEGA 2560 microcontroller is used to implement the MPPT algorithm and
(b)
Figure 6. I − V characteristics of the PV module (a) for (G, T ) =
(270W/m2 , 430 C) and (b) for (G, T ) = (480W/m2 , 480 C)
Table I
PARAMETERS OF DESIGNED SEPIC CONVERTER
Sl.No.
1
2
3
4
5
6
7
Parameter
L1
L2
Cin
C1
C2
fs
RL
Value
180µH
180µH
440µF
47µF
220µF
50kHz
15Ω
Converter output voltage measurement is required for implementation of the MPPT algorithm and the microcontroller
board cannot tolerate more than 5 V. The converter output
voltage (Vo ) is measured using the voltage divider circuit with
resistances R1 and R2 of values 10 kΩ and 1 kΩ respectively.
The PV module ELDORA 40-P is used for the experimental
setup as shown in Fig. 5 and the experiment is performed using
artificial insolation with the help of halogen and incandescent
lamps.
The output voltage sensor based MPPT technique with fixed
step size of ∆D = 1% and perturbation time of Ta = 20ms
is tested for a step change in insolation level from 270 W/m2
to 480 W/m2 . The measured I − V characteristics of the
considered PV module at (G, T ) = (270 W/m2 ,43o C) and at
(G, T ) = (480 W/m2 ,48oC) are shown in Fig. 6. From the
experimental I − V characteristics it can be observed that
the voltage corresponding to MPP for the above mentioned
insolation and temperature conditions are 15.5 V and 16.5 V
respectively. The startup tracking waveforms for (G, T ) = (270
W/m2 ,43o C) and for (G, T ) = (480 W/m2 ,48o C) are shown in
Fig. 7(a) and Fig. 7(b) respectively. From Fig. 7(a) and Fig.
7(b) it can be observed that the MPPT method is effectively
tracking the maximum power from the PV module. Fig. 7(c)
shows the tracking waveforms for a change in insolation and
temperature from (G, T ) = (270 W/m2 ,43o C) to (G, T ) =
(480 W/m2 ,48o C) and the tracking waveforms for a change in
insolation and temperature from (G, T ) = (480 W/m2 ,48o C)
to (G, T ) = (270 W/m2 ,43oC) are shown in Fig. 7(d). From
Fig. 7(c) and Fig. 7(d) it is worth to mention that the MPPT
method with output voltage sensor is able to track the MPP
accurately even for a change in insolation. To validate the
tracking performance of the MPPT algorithm with respect
to load variation, experiment is conducted by changing the
load for (G, T ) = (480 W/m2 ,48o C) and the corresponding
tracking waveforms are shown in Fig. 7(e). From Fig. 7(e) it
is worth to mention that the output voltage sensor based MPPT
algorithm is robust to load variations. Thus an efficient MPPT
algorithm can be implemented with reduced cost using only
a single voltage sensor at the output. For clear observation of
steady state behaviour of the MPPT algorithm, experiment is
performed by considering Ta = 1s and ∆D = 1% for (G, T ) =
(270 W/m2 ,43o C) and the corresponding tracking waveforms
are shown in Fig. 8. From Fig. 8 it can be visualised that the
operating point moves in three points surrounding the MPP
in steady state and the output voltage (Vo ) variation is less
compared to VP V because the converter operates in step down
mode. The comparison of output voltage sensor based MPPT
method with the two widely used methods P&O and IncCond
is presented in Table. 2.
Table II
C OMPARISON OF OUTPUT VOLTAGE SENSOR BASED MPP WITH P&O AND
I NC C OND METHODS
Sl.No.
parameter
P&O
IncCond
1
Sensors
2
Steady
state
operation
Implementation
cost
Accurate
Voltage &
Current
3-Level [6]
Medium
Voltage &
Current
3-Level
[10]
Medium
Yes
Yes
3
4
(a)
(b)
(c)
output
voltage
sensor
based
Voltage
3-Level
Low
Yes
it is observed that with a single sensor at the output of the
converter an efficient, simple and low cost MPPT algorithm
can be implemented.
R EFERENCES
(d)
(e)
Figure 7. Tracking waveforms with output voltage sensor based MPPT
(a) startup for (G, T ) = (270 W/m2 ,43o C) (b) startup for (G, T ) = (480
W/m2 ,48o C) (c) for a change in Solar insolation from (G, T ) = (270
W/m2 ,43o C) to (G, T ) = (480 W/m2 ,48o C) (d) for a change in Solar insolation from (G, T ) = (480 W/m2 ,48o C) to (G, T ) = (270 W/m2 ,43o C) and
(e) tracking waveforms with load variation for (G, T ) = (480 W/m2 ,48o C).
Figure 8. steady state 3-level operation for (G, T ) = (270W/m2 , 430 C).
IV. C ONCLUSION
In this paper output voltage sensor based MPPT algorithm
by considering direct duty ratio control method with SEPIC
converter is presented. The experimental results prove that the
proposed system is effectively tracking the maximum power
from the PV module. Moreover the robustness of the MPPT
technique to load variations and simple algorithm are the
merits of this tracking algorithm. From the results obtained
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