Download A new maximum power point tracking approach for decreasing

A new maximum power point tracking approach
for decreasing convergence time
Mustafa Engin Başoğlu, Bekir Çakır
Department of Electrical Engineering, Kocaeli University
Kocaeli, Turkey
[email protected], [email protected]
Abstract— This study presents a new maximum power point
tracking (MPPT) approach for solar panels. By using voltage
current characteristic of solar panel, some analytical approaches
have been developed. With the help of this approach,
determination of initial operation point has been improved. In
other words, this point has been determined by making some
assumptions. Thus, one of the challenging tasks related to MPPT,
convergence time is reduced. Benefits of developed approach
have been shown by making a comparison with the Perturb and
Observe (P&O) and Incremental Conductance (IC) algorithm. In
this context, a low power boost converter has been designed with
direct duty control in order to verify the proposed approach.
Experimental results show that proposed approach performs
better than conventional ones. While convergence time is high in
case of P&O and IC usage, with proposed approach, it is reduced
remarkably. Besides, steady state oscillation is almost eliminated
in proposed approach.
Keywords— Maximum power point tracking (MPPT), Perturb
and Observe, Incremental Conductance, solar panel, convergence
time, hybrid method.
I. INTRODUCTION
Electricity demand increases continuously with industrial
and technological developments. In order to meet this demand,
different approaches have been used by countries. These are
summarized as to diversify the resources in electricity
generation, increase the energy efficiency and improve the
power system performance. In addition, it is expected that cost
of these approaches should not be high with respect to its
advantage. In this context, solar power generation (SPG)
system is an important alternative to electricity generation due
to the unlimited nature, cost of free and eco-friendly
nowadays. Although the main drawback of the SPG system is
the installation cost, with the last developments in the last
decade, this cost greatly decreases and is expected to continue
to decrease in the future [1,2].
Power conversion efficiency and capacity factor are
significant parameter for solar panels. On the one hand, power
conversion efficiency of solar panel is the ratio of actual
power and theoretical power per one square meter. On the
other hand, capacity factor defines the ratio of actual energy
and theoretical energy. In order to increase this parameter,
solar panels must be operated under its maximum power point
(MPP). However, voltage-current (V-I) characteristic of solar
panels is not linear and there is one unique point on the V-I
curve of solar panel that MPP operation is realized. Therefore,
so as to realize MPPT, many algorithms have been proposed
in literature [3-17].
The most conventional algorithm, constant voltage
method, does not take into account changes in solar irradiance.
Therefore, this algorithm can be used under minor changes in
solar irradiance. Perturb and Observe (P&O) and incremental
conductance (IC) are online algorithms which are very popular
in terms of ease of implementation and high tracking
efficiency. However, with higher tracking success under
rapidly changing atmospheric condition, IC performs better
than P&O. Furthermore, these algorithms have the same
problem related to oscillation at MPP and convergence time
(response time) which can be defined as a paradigm in MPPT.
In order to solve this paradigm, improved versions of these
algorithms have been presented [3-12]. These approaches are
generally based on the determination of operation point of
solar panel and generation of control command with respect to
this point. On the other hand, there are more conventional
approaches such as short circuit current and open circuit
voltage measurement based methods. For these approaches,
additional hardware requires which increase the cost of the
system. Besides, tracking capability is low due to the
dependency of some coefficients which are not constant and
estimated easily [13]. Some techniques such as neural
network, fuzzy logic and genetic algorithms are also used.
Studies with these approaches increase the tracking efficiency
and may decrease convergence time. However, complexity
and microcontroller requirement increase [14-17].
There are many problems required to be solved related to
MPPT. One of the problems is the reducing the convergence
time. For the purpose of coming up with this problem, hybrid
approaches are used. Therefore, dynamic tracking efficiency
increases. In this study, a new hybrid approach has been
developed by combining the conventional IC and analytical
approach for initialization. Proposed approach is developed in
order to reduce the convergence time. On the other hand, IC is
used for providing the high tracking accuracy. Remains of the
paper are as follows. Some conventional MPPT methods are
presented in Section II. Developed methods are explained in
detail in Section III. Comparative results of P&O, IC and
proposed method are presented in Section IV. Finally some
key points of this study are drawn in the last section.
978-1-4799-7993-6/15/$31.00 ©2015 IEEE
II. MPPT METHODS
There are several criterions that determine the performance
of MPPT. Convergence time is one of them and it means to
time of reaching to new MPP. In order to show the
performance of the proposed approach, two conventional
algorithms are selected for comparison. In this section, P&O
and IC are explained briefly.
A. Perturb and Observe Algorithm
P&O is one of the hill climbing based algorithms. In this
algorithm, it is intended to reach the peak point of voltagepower characteristic curves. For this purpose, current and
voltage of solar panel are measured and power is calculated in
a cycle time. As shown in Fig. 1, reference value of voltage is
adjusted by voltage and power value that is obtained by
measurements. For this algorithm, there are five possible
conditions. If old and new power is equal to each other,
maximum power point tracking is realized and there is no
need to change reference voltage. If these power are not equal,
voltage comparison are made. If voltage and power change in
the same sign (positive or negative), reference value of voltage
is increased. Voltage of PV module is decreased in case power
and voltage change in opposite sign [3-6].
better than P&O under rapid changes in solar irradiance [1012]. For this algorithm, derivative of power with respect to
voltage can be defined as a control index. In order to realize
MPP operation, this index must be approximately zero. On the
other hand, if this index bigger than zero, it can be said that
MPP is on the left of the MPP and vice versa as given in Fig.
3. All these scenarios can be defined as formulated in (1)-(3).
dP
dV
dP
dV
dP
dV
=0→
>0→
<0→
ΔI
ΔV
ΔI
ΔV
ΔI
ΔV
=−
>−
<−
I
V
→ MPP
I
V
I
V
Fig. 2. Flowchart of IC algorithm (duty cycle of PWM based)
Fig. 1. Flowchart of P&O algorithm
B. Incremental Conductance Algorithm
IC is another hill climbing based algorithm. In this
algorithm, same hardware can be used. Main difference from
P&O is the unnecessary of power calculation. Instead of this
calculation, additional comparison stages are included for this
algorithm as presented in Fig. 2. In this context, incremental
and instantaneous conductance must be calculated in every
cycle. On the other hand, it is worth noting that IC performs
Fig. 3. Voltage-power (V-P) characteristic curve
(1)
(2)
(3)
III. PROPOSED MPPT APPROACH
Usage of boost converter is very common in a MPPT
application due to the simple design and ease of its control.
Therefore, a boost converter has been designed with a new
MPPT approach in this study. The main purpose of the
developed approach is to make a good initialization in terms
of initial operation point of solar panel. For example, as
presented in Fig 4, point G is not an efficient point for solar
panel. Therefore, operation point of solar panel should be
moved from G to MPP under any environmental condition.
Furthermore, it is worth noting that convergence time to MPP
is based on the first position of initial operation point. Thus,
this first point should be determined well.
boost converter, D is the duty ratio of PWM signal and Rload is
the load resistance. As can be seen in (7), RPV can be changed
by the variation of D.
When it comes to our proposed approach, the first step is
the determination of the position of initial point by taking two
random sampling. In these samplings, voltage and current of
solar panel are measured and power is calculated. Then, by
calculating the derivative power with respect to voltage, it is
understood that whether initial point is on the right or left of
the MPP. Finally, initial value of duty ratio of PWM signal is
calculated. These two options are based on solar panel current
and constant voltage method, respectively. Fig. 5 presents the
flowchart of the proposed method.
Fig. 4. V-I curve of solar panel
Equivalent resistance seen from input of boost converter is
the ratio of voltage and current of solar panel. In fact,
changing this resistance provides the MPPT realization. For
fixed load resistance conditions, this resistance depends on
one parameter which is the duty ratio of pulse width
modulation (PWM) signal. By using typical equations of boost
converter in (4)-(6), equivalent resistance of boost converter
can be obtained as given in (7) [18].
Fig. 5. Proposed approach
RPV =
Vo = Vi
VPV
V
= i
Ii
I PV
1
1− D
= I o Rload
VPV = I PV RPV
V
2
RPV = o (1 − D )
Io
(4)
(5)
(6)
(7)
where RPV is the equivalent resistance seen from input of
converter, VPV and IPV are the voltage and current of solar
panel, Vi and Ii are the input voltage and input current of boost
converter, VO and IO are the output voltage and current of
In our approach, for a typical V-I curve of solar panel, if
initial operation point is on the right of the MPP which
depends on load resistance, constant voltage method is used.
For this method, since range of voltage is limited on the right
of the MPP, values of solar panel under standard test
conditions (STC) are used. In this context, duty ratio of PWM
signal is calculated as given in (8).
D = 1−
Vmpp ( STC )
I mpp ( STC )×Rload ×η
(8)
where Vmpp(STC) and Impp(STC) are the voltage and current of
solar panel under STC. If initial operation point is on the left
of the MPP, duty ratio can be calculated as given in (9).
D = 1−
Rmpp (Q)
Rload ×η
(9)
where Rmpp(Q) is the equivalent resistance of solar panel. In
this context, this resistance is calculated based on the accuracy
requirements. For high accuracy, number of calculated
resistance should be increased. This resistance is calculated
under different solar irradiance condition. Then, value of this
resistance is selected based on the current of solar panel. In
other words, a look up table can be prepared based on the
current and solar irradiance. Thus, value of Rmpp(Q) is selected
as reference for initialization. After this initialization, IC
algorithm is used to reach MPP under given conditions for
obtaining high tracking accuracy [19].
IV. EXPERIMENTAL STUDIES
In order to show the advantage of the proposed approach, a
boost converter has been designed. As listed in Table 1,
nominal power of this converter is 90W which is also
maximum power of solar panel under STC. Furthermore, the
other components are listed as given in Table 1. Fig. 6 shows
the designed hardware.
TABLE I.
Fig. 7. Result of P&O algorithm
On the other hand, plane of module irradiation decreases
compared with the first condition by 10% during second
experiment with IC. However, convergence time is
approximately same as presented in Fig. 8. It is worth noting
that since theoretical power is higher in Exp. 1, for the same
solar irradiation condition, it is estimated that convergence
time is expected lower in P&O than in IC.
SPECIFICATION OF CONVERTER
TABLE II.
Specifications
Converter Type/Power
Inductance
Output Capacitor
Power Switch/Diode
Current Measurement
Voltage Measurement
Microcontroller
Boost/90Wp
1mH
68uF
IRFP450/MUR840
LTS-NP25
Voltage Divider Circuit
PIC18F452
EXPERIMENTAL STUDIES
Results
Solar Irradiation (W/m2)
Theoretical Power (W)
Actual Power (W)
Tracking Efficiency (%)
Convergence Time (msec)
Output Voltage (V)
Output Current (A)
Load Resistance (Ω)
Output fluctuation
Exp. 1
(P&O)
730
51.8
48.6
93.8
~40
36
1.35
27
Moderate
Exp. 2
(IC)
590
41.9
38.4
91.6
~40*
34
1.13
30
Exp. 3
(Proposed)
670
47.5
46
96.8
~12
39
1.18
33
Low
*
Solar Irradiance is low
Fig. 6. Photo of designed hardware
In our experimental studies, first of all, P&O and IC
algorithm were used. These experiments were named as Exp.
1 and Exp.2 as listed in Table 2. In this context, same
hardware was used. Measurements were taken from output of
the boost converter. By considering the efficiency of converter
and plane of module irradiation, theoretical power can be
estimated. Type of load was selected as pure resistor which
changes from 27 ohm to 33 ohm. On the other hand, plane of
module irradiation was almost same within the measurement
period. As presented in Fig. 7, in case of usage P&O,
convergence time is 40 msec. Furthermore, fluctuation at
steady state condition is rather low in this case.
Fig. 8. Result of IC algorithm
As presented in Fig. 9, in case of proposed approach usage,
convergence time is remarkably reduced compared with the
two conventional algorithms. In this condition, this time is
calculated as 12 msec. Furthermore, value of load resistance is
another parameter affecting the convergence time. For high
load resistance condition, convergence time increases. In these
experiments, value of load resistance is the highest in the
proposed method. However, due to the benefits of the
proposed approach, this time takes lower value than the other
methods. On the other hand, fluctuations in the proposed
method are also moderate as in conventional methods are.
Tracking efficiency is also improved as listed in Table 2.
[5]
[6]
[7]
[8]
[9]
[10]
Fig. 9. Proposed approach
[11]
V. CONCLUSIONS
In this study, a new MPPT approach has been presented.
The contribution of this paper is to reduce convergence time
(response time) by using analytical approach with the help of
V-I characteristic curve of solar panel. In order to show the
performance of the proposed method, a boost converter has
been designed and carried out. Two conventional MPPT
algorithms have been used to make a performance comparison
in terms of convergence time, steady state fluctuation and
tracking efficiency. Experimental results show that the lowest
convergence time and highest tracking efficiency is obtained
in the proposed approach compared with the P&O and IC
algorithm. The future work of this study is to develop new
approach related to partial shading condition with low
convergence time.
[12]
[13]
[14]
[15]
[16]
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