A COMPARATIVE SIMULATION ANALYSIS OF MAXIMUM POWER POINT TRACKING APPROACHES
Chee Lim Nge1,2, Georgi Yordanov1,2, Ole-Morten Midtgård1, Tor Oskar Sætre1, Lars Norum2
University of Agder, Faculty of Engineering and Science, Grooseveien 36, 4876 Grimstad, Norway
2
Norwegian University of Science and Technology, Department of Electric Power Engineering, 7491 Trondheim, Norway
E-mail: chee.l.nge@uia.no
1
ABSTRACT: The occurrence of multiple local maxima due to partial shading conditions poses a serious challenge to
MPPT techniques. This paper compares the popular real-time MPPT algorithm with the scanning approach using
PSPICE simulation. The MPPT methods are compared at dynamic partial shading conditions. The compromises
between real-time and scanning methods are investigated. It is shown that the scanning approach is able to search for
global MPPs but incurs power loss during the scanning period. A new strategy that reduces the scanning period by
skipping parts of the voltage range is presented in this paper.
Keywords: shading, inverter, photovoltaic
1
INTRODUCTION
There have been a large number of publications on
maximum power point tracking (MPPT) methods and the
research interest has continuously grown in the recent
past [1]. MPPT contributes greatly to the overall
efficiency of photovoltaic (PV) inverters, which in turn is
an important factor for the economic viability of the
system. The occurrence of multiple local maxima due to
the partial shading conditions poses a serious challenge
to MPPT techniques. This problem is more profound in
urban installations, which recently have increased in
demand due to government subsidies. The reductions in
energy yield due to the limitations of MPPT techniques
under partial shading conditions are confirmed in reports
based on field data [2-5].
If we consider only true MPPT techniques that are
not dependent on a specific PV module, they can be
grouped into two categories: the real-time and the
scanning approaches. The real-time MPPT techniques
include the popular perturb-and-observe [6-8] and the
incremental-conductance (IncCond) [9, 10] methods.
They have fast responses as they are able to continuously
track peak power under rapidly changing atmospheric
conditions. However, such approaches have no means of
detecting global peak power and they only move the
operating point to the nearest local maximum point.
The scanning techniques are capable of tracking the
global peak power because they periodically search
throughout the full possible operating range. One
straightforward approach is to characterize the I-V curve
using current sweep waveform [11]. The converter is
disabled during the sweep in order to reduce the sweep
period. Advanced search algorithms using a Fibonacci
sequence [12] and particle swamp optimization technique
[13] are proposed to reduce the amount of operating
points for MPP evaluation. However they do not
necessarily reduce the scanning period because such
algorithms need to randomly search through the possible
range before reaching steady state.
Since scanning techniques are initiated periodically,
they lose track of the MPP between the scanning periods.
Reference [14] tracks MPP using perturb-and-observe in
real-time but scans for global peak power occasionally
when sudden change in irradiance occurs. Since it stops
the scanning when the subsequent peak is lower than the
previous peak, this approach would miss a distant global
maximum point at higher voltages. On the other hand, a
two-stage approach that first moves the operating point to
the vicinity of the global peak power on the PV load line
tends to miss global peak power that lies to the left side
of the load line [15].
It is obvious that there are compromises amongst the
MPPT approaches under dynamic atmospheric and
partial shading conditions. This paper provides a
comparative analysis between real-time and scanning
approaches. Moreover, a new scanning strategy is
proposed, which reduces the time for tracking global
peak power by skipping parts of the voltage range.
2
SIMULATION SETUP
Figure 1 is the popular two-stage inverter
configuration suitable for grid-connected PV systems.
The boost converter stage sets the operating point of PV
module and it is controlled by the MPPT control unit.
The full-bridge inverter keeps the dc-link voltage
between the two stages constant by adjusting power flow
into the grid. For this simulation analysis, the power
stage is simplified to a boost converter with constant
voltage load. This is assuming that the full-bridge
inverter has fast response.
Photovoltaic
Boost
Converter
Full-bridge
Inverter
Grid
MPPT
Control
Control
Figure 1: Two-stage grid-connected PV inverter
The PV system is modeled using the circuit-oriented
simulation software, PSPICE. It is widely used in power
electronics applications because of its effectiveness in
simulating analog circuits. In order to illustrate the
tradeoffs amongst various MPPT approaches, the
following techniques are compared:
a. IncCond is selected to show the fast dynamic
response of real-time approaches.
b. Combination of IncCond with a simple
scanning approach that utilizes voltage sweep
waveform to periodically characterize the I-V
curve and track the global peak power.
c.
Combination of IncCond with the new
proposed scanning method, which skips parts
of the voltage range
2.1 Boost converter
The schematic consisting of the main blocks of the
boost converter PSPICE model is shown in Figure 2. The
power stage is considerably simplified to optimize the
computational efficiency. The power devices are
represented by ideal diodes and switches. The full-bridge
inverter stage is modeled as a voltage source connected to
an R-L filter that simulates the transient response.
Ctrl1
shading condition as depicted in Figure 4. The
characteristic curves correspond to the PV string model
in Figure 3. The global peak shifts from 189W at 97V to
207W at 74V when IPV1 increases from 2.5A to 3.0A.
This corresponds to irradiance variation of 100W/m2
within 100ms. The results are presented in Section 4.
n = {nd*ns}
is = {is}
IPV1
TD = 500m
TF = 100m
TR = 100m
I1 = 2.5
I2 = 3.0
Ctrl2
VREF
VREF
MPPT
PWMA1
PWMA1
PWMA2
PWMA2
VIN_P
Lin
PV1
Rlin
PV_POS
Dbp2
Rsh1
Dpv3
Dbp3
Dpv4
Dbp4
Dpv5
Dbp5
vocm = 22.3
is = {5/nVT}
nd = 1
ns = 36
n = {nd*ns}
is = {is}
n = {nd*ns}
is = {is}
Rsr5 PV_NEG
Rsh5
Figure 3: PV string model
S1
VIN_P
PV_NEG
Dpv2
PV_POS
PARAMETERS:
SW VoltMode
VIN
PWMA1
+
D1
Cin
D1_
Rcb
D2_
VOUT
S2
PWMA2
PV
IPV5
2Adc
Dbp1
n = {nd*ns}
is = {is}
VIN
VIN_P
Rsr1
Dpv1
n = {nd*ns}
is = {is}
1
+
D2
2
Rinv
Cout
Linv
Vdc-link
0
Figure 2: Main schematic of the PSPICE model
The VOLTMODE hierarchical block is the single
loop voltage mode controller that generates PWM signals
by comparing the input voltage, VIN_P with the reference
signal, VREF. The MPPT control unit measures the
current and voltage of the PV modules, and tracks the
MPP by sending VREF to the VOLTMODE controller.
Considering that each power switch is connected to an
anti-parallel diode, the synchronous boost converter
always operates in the continuous conduction mode. The
input voltage control of the boost converter becomes
similar to buck converter output voltage control if the
switching duty ratio of S1 is used as the control output.
As a result, the controller is considerably simplified since
the duty-cycle to input-voltage transfer function is always
linear.
2.2 PV modules
Figure 3 depicts the PSPICE model of a PV string
with 5 modules connected in series. Each PV module
consists of 36 cells connected in series. It has an opencircuit voltage of 22V and a short-circuit current of 5A.
The PV module is modeled as a current source, IPV
connected in parallel with a diode, DPV. For simplicity,
the irradiance level is directly proportional to the
photocurrent, IPV. The series and shunt resistances, RSR
and RSH model the fill factor losses. It is assumed that the
first 4 modules have identical characteristics and
irradiance hence IPV1, RSR1 and RSH1 are lumped
parameters. For simplicity, there is only one bypass diode
(DBP1-5) connected in parallel with each module since the
irradiance is assumed to be uniform on each module.
The MPPT is evaluated under the dynamic partial
Figure 4: Power-voltage characteristic of a PV string
3
PROPOSED MPPT METHOD
As previously discussed, it is necessary to scan the PV curve of the PV modules in order to find the global
peak. Figure 5 shows the simplified P-V curves that
consist of two local maxima under partial shading
conditions. It represents a PV string that is illuminated
with different irradiance levels. The blue dashed lines
correspond to constant current where the photocurrent
IPV1 is larger than IPV2. The valid input voltage range of
the boost converter is between VMIN and VMAX.
are shown in Figures 6 and 7:
a) Incremental-conductance, IncCond.
b) Combination of IncCond with voltage sweep.
c) Combination of IncCond with the new
scanning method proposed in the present paper.
IPV2
IPV1
PMPP
JUMP to VEST
VMIN
VMAX
(a)
IPV1
PMPP
VEST>VMAX
IPV2
VMIN
VMAX
(b)
Figure 5: Proposed MPP voltage estimation approach
The proposed scanning trajectory is indicated as the
green dashed line in Figure 5. The sweep starts at VMIN
and the peak power is continuously updated while the
operating point moves towards higher input voltage. The
instantaneous PV current, IPVx decreases as the input
voltage increases. Once a local maximum power PMPP1 is
detected at lower voltage level, parts of the P-V curve at
higher voltage can be avoided. For a given IPVx the lowest
voltage at which a higher MPP is possible can be
estimated from equation (1). This is to assume the ideal
condition where IPVx remains constant up to the MPP.
VEST =
PMPP1
I PVx
(1)
As shown in Figure 5a, parts of the curve below
PMPP1 are avoided using the JUMP to VEST operation. It
should be noted that JUMP to VEST operation does not
necessarily occur when current is equal to IPV2. As long
as IPVx is less than IPV1, JUMP to VEST operation might
occur.
The operating point continues to move towards
higher voltage level as long as VEST does not exceed the
upper voltage range of the converter, VMAX. Referring to
Figure 5b, the scan stops when VEST is larger than
VMAX. The lower level local MPP at higher voltage is
avoided in this case.
It is important to note that the proposed algorithm
assumes static P-V curve during the scanning.
4
RESULTS
PSPICE simulation results that compare different
MPPT methods on the system presented in Section 2.2
Figure 6: MPPT comparison: IPV1 increases to 3.0A
Method b) and c) search for the global peak using a
scanning approach and then they move the input voltage
to the vicinity of the global MPP voltage after the sweep.
They track MPP in real-time using the IncCond method
between the scanning periods. The scanning mechanisms
are initiated every 1s and they sweep the input voltage at
the slew rate of 0.15V/ms. The boost converter minimum
input voltage is selected at 70V and this is where both
scanning operations start. The voltage sweep method of
b) is a simple periodic sweep of PV voltage that stops
when the PV current drops to less than 0.5A. The
proposed method in c) JUMPs to VEST every 40ms and it
stops scanning when VEST is larger than VMAX.
proposed method reduces the energy loss during
scanning period by approximately 65%.
IV. “JUMP to VEST” is initiated 40ms after t2 and this
is where VIN waveforms of the proposed method
lead those of method b)
V. For method b), PIN drops to approximately 50W,
when the operating point moves towards opencircuit voltage before scanning stops at t4. This
results in a considerable power loss. For the
proposed method, PIN does not need to deviate
significantly from MPP.
There are tradeoffs in selecting the interval of the
scanning mechanism. Hypothetically, it is necessary to
initiate scanning immediately after global peak shifts to
another local maximum point. It needs to scan again if
the global peak varies during scanning or immediately
after that. On the other hand, there are power losses
during scanning as PIN deviates from MPP. Also, scan
should be avoided if it is not under partial shading
conditions.
One possible solution is to initiate the scanning
mechanism adaptively when a considerable variation in
local MPP is detected. This is an indication of the shift of
global peak. However, the MPP variation due to
irradiance change could be too small and it is difficult to
distinguish from IncCond perturbation. The PIN
increment in Figure 6 at t1 is less than 10W.
5
Figure 7: MPPT comparison: IPV1 decreases to 2.5A
Figures 6 and 7 show that method c) yields the
highest average input power PIN to the boost converter.
Other important observations from the comparative
simulation results are:
I. After the irradiance (i.e. IPV1) changes at t1, the
global MPP voltage shifts from 74V to 97V or
vice versa. Both methods b) and c) are able to
calibrate the tracking voltage to the global peak
but method a) does not.
II. The scanning starts at t2 after IPV1 changes. The
three MPPT techniques are identical between t1
and t2 because they track MPP using the same
approach i.e. the IncCond method.
III. The power PIN deviates from global peak during
the scanning periods. For method b) the scanning
period is between t2-t4 while the proposed method
is between t2-t3. At IPV1 = 2.5A, there is about
100ms difference between method b) and the
proposed method. At IPV1 = 3.0A, the proposed
method completes scanning faster than method b)
by about 150ms. Compared to method b), the
CONCLUSIONS
The comparative simulation results verify that the
real-time approaches such as IncCond are not able to
track global MPP. It is shown that IncCond locks to local
maximum point as it has no means of detecting global
peak power. The global peak can be found by scanning
through the voltage range. However, if the power losses
of the scanning mechanisms are significant, the time
interval between scanning instants needs to be relatively
large. This in turn results in poor response if the global
peak shifts among local maxima rapidly. On the other
hand, it is necessary to scan immediately after global
MPP moves to another peak.
The proposed MPPT method is evaluated using a
simplified PV string model that operates under dynamic
partial shading condition. The capacitances of the PV
modules and the interconnect inductances are not
considered in the modeling. Compared to the simple
voltage sweep approach, the proposed method reduces
the energy loss during scanning period by approximately
65%. The new method prevents the scanning from
drifting to open-circuit voltage level where the power is
low, and this is done by comparing the next possible
MPP voltage, VEST to VMAX.
6
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