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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 29, NO. 12, DECEMBER 2014
A Simple Energy Recovery Scheme to Harvest
the Energy from Shaded Photovoltaic
Modules During Partial Shading
Mohd. Zulkifli Ramli and Zainal Salam, Member, IEEE
Abstract—This paper proposes a simple circuit to recover the
energy that otherwise would be lost due to the partial shadings
on photovoltaic (PV) modules. Since the circuit can be readily
retrofitted to an existing PV system, no modification on the central
inverter is required. The main idea of the scheme is that, during
partial shading, parts of the current from the nonshaded modules
are harvested by an energy recovery circuit using power electronic
switches and storage components. In doing so, the current of the
PV string is maintained at the level generated by the shaded module. There is no need for the shaded module to be short-circuited;
as a result, it can still actively produce output power (despite being
partially shaded). To investigate the idea, the proposed circuit is
retrofitted to a prototype PV system using eight modules. The partial shading conditions are emulated using a solar simulator with
a controllable irradiance capability. The results are validated by a
good agreement between the experimental and simulation works.
Index Terms—Energy recovery, inverter, maximum power point
(MPP), maximum power point tracking (MPPT), partial shading,
photovoltaic (PV).
I. INTRODUCTION
OR many years, the central inverter has been the preferable choice for large as well as small photovoltaic (PV)
system installations [1], [2]. In this configuration, a number
of PV modules are connected in series to form a string. Several of these strings are arranged in parallel to form an array,
which is then connected to one central inverter. This is known
as series-parallel connection and is a typical setup for the PV
power generation system. The merits of the PV system with
central inverters are well known: simple installation, less maintenance, and high reliability [3], [4]. However, it does exhibit
several disadvantages, one of which is the severe reduction in
the throughput power when one or a number of modules are subjected to partial shading [1], [5]–[11]. In the building integrated
F
Manuscript received April 25, 2013; revised September 2, 2013 and December 1, 2013; accepted January 7, 2014. Date of publication January 24, 2014;
date of current version August 13, 2014. This research was supported by the
Ministry of Higher Education Malaysia, under the Research University Grant
2423.00 G40. The project is managed by the Research Management Centre, Universiti Teknologi Malaysia. Recommended for publication by Associate Editor
V. Agarwal.
M. Z. Ramli is with the Faculty of Electrical Engineering, Universiti Teknikal
Melaka,76100 Melaka, Malaysia (e-mail: mohd.zulkifli@utem.edu.my).
Z. Salam is with the Centre for Electrical Energy Systems, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia.
(e-mail: zainals@fke.utm.my).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TPEL.2014.2302007
PV system, the shading normally originates from the nearby tree,
building, chimney, power line poles, or similar objects. These
factors may be unavoidable due to the building congestion in
urban areas and unforeseen erection of new structures. In a large
PV power generation system (PV farm), the partial shading can
be caused by clouds that strike on certain spots of the solar
array, while other parts are left uniformly irradiated. In certain
cases, the remains of birds or animals cause the shading on the
modules. Another source of partial shading-like characteristics
is exhibited by module irregularities; a common example would
be the presence of cracks on one or more modules of the PV
array.
With the presence of partial shading, the behavior of the PV
system becomes very complicated. This is because the shaded
module acts as a load instead of a generator; consequently, a hot
spot is created and if left unprotected, the module may experience irreparable damage. Typically, every module is connected
to a bypass diode to divert the current in the case of partial shading occurrence. However, when the bypass diode is activated,
the P –V characteristic curve exhibits multiple peaks, i.e. several
local along with one global peak [5], [6], [12]–[15]. If the system
is equipped with the conventional maximum power point tracking (MPPT) such as perturbed and observed (P&O), increment
conductance or Hill-climbing, it would be very difficult to track
the true maximum power point (MPP) peak because these algorithms could not discriminate between the local and the global
peaks. In most cases, the MPPT will settle at a local peak,
possibly resulting in a huge loss of power [1], [6], [16]–[18].
Furthermore, when the current flows through the bypass
diode, conduction losses occur, further degrading the system’s
efficiency.
There are efforts using sophisticated MPPT schemes such as
modified P&O [6], [19]–[22], particle swarm optimization [13],
[20], [23], ant colony optimization [24] and the direct search
method [25]. Despite the success of these algorithms to track
the global peak [13], [23], [26], it must be noted that as long
as the shaded module is being short-circuited by the bypass
diode, it is totally unusable. However, the shading phenomena
may not always be so severe such that the module receives
zero irradiance. It is known that, depending on the severity
of the shading, there is a certain amount of power that could
possibly be captured by the shaded module. Despite this fact,
the opportunity to harvest this power is lost due to the activation
of the bypass diode.
Hence, various methods are devised to recover the power
from the shaded module. One approach is to place a small
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RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
dedicated dc–dc converter to every module; then these modules are connected to the central inverter [5], [12], [26]–[28].
In the literature, this method is known as the distributed MPP
configuration. The converter normally has a power rating approximately equal to the module itself and is equipped with its
own MPPT controller. Using this scheme, the nonshaded modules are not affected by the shaded ones, and the power from
the latter can be independently harvested. Although attractive,
the method inhibits several shortcomings. During normal operation, the converter conducts the full load current, resulting
in high conduction and switching losses [28]. Furthermore, the
reliability of the electronic components is reduced due to their
exposure to harsh environment conditions, particularly high operating temperature. This is unavoidable since the converter is
mounted underneath the module itself [29], [30]. Alternatively,
there are considerable efforts to develop the dc–ac converter for
each module (known as microinverter), which is directly connected to the ac grid [3], [26], [27], [31]–[37]. Using the concept,
the central inverter is not required because the microinverter has
its own MPPT and inversion and voltage step-up mechanism.
Another method to utilize the power from the shaded modules
is proposed by the authors in [38]. In this technique, a bidirectional buck–boost, flyback or Cuk converter is used to divert
the current of the nonshaded modules by controlling the duty
cycle of the converters. During partial shading, the energy from
the nonshaded modules is transferred to the inverter and consumed by the PV system. The work in [30] only demonstrates
the workability of the approach using two modules per converter. However, to accommodate more than two modules, the
converters need to be overlapped to allow for the string current
from the nonshaded module to be properly diverted. As a result, for every interconnection between a group of two modules,
additional two switches and two diodes are required. A similar
scheme, albeit using a different circuitry, has been proposed by
Shimizu et al [14]. Despite its effectiveness, the main drawback
of the scheme is the switching limitation; for example, for four
modules in series, the off duty cycle range is limited to 25%.
For higher number of modules, the off duty cycle is even lower.
This is because within a single switching cycle, only one switch
is forced to be turned OFF, while others remain ON. The limited off duty cycle restricts the ability of the circuit to control
the power flow under severe shading condition. In addition, although the scheme utilizes MPPT to improve the efficiency of
the circuit, the authors do not mention its performance during
partial shading and how it is synchronized to the MPPT of the
central inverter. There are also concerns regarding the accuracy
of the voltage and current sensors (used for MPPT computation)
when subjected to the high temperature beneath the modules.
In [39], an alternative method using a single inductor per
four modules is proposed. Despite the reduced inductor, the circuit requires a large number of switches and diodes, i.e. for a
four-module system, eight switches and ten diodes are needed.
Furthermore, during the inductor charge and discharge cycles,
only one combination of switches and diodes is switched ON
and OFF; others are not active. Under this constraint, the best
switching combinations have to be found in order to deliver
the maximum power during partial shading. However, in many
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cases, the search for the optimum switching configuration is
complex and requires a substantial amount of time. Thus there
are possibilities that the algorithm may not be able to cope with
rapidly changing cloud condition. For example, as described
in [25], the fluctuation in irradiation can go up to 15 times within
1 minute. If the partial shading occurred during this period, an
efficient tracking could not be guaranteed. More recently, an
energy recovery scheme for shaded module for the multilevel
inverter is reported [40]. Despite its ability to harvest the power
during partial shading, the buck converter always conducts at full
load current during a normal condition. This causes high switching and conduction losses. Another drawback of this technique
is the complexity of the switching due to the multilevel inverter
structure.
With regard to these issues, this paper describes an attempt to
improve the capabilities of the topologies described above. The
proposed scheme is based on a group of four modules (one unit),
but can be extended to accommodate a large number of modules
by combining other units using a simple interconnecting circuits.
The number of switches for four modules (one unit) is 1, and
for the interconnection of two units, an additional two switches
and one inductor are needed. The circuit is only active during
the event of partial shading; during uniform irradiance, it is
isolated from the PV system. Besides, the switching pattern
for the switch is simple, i.e. it operates based on an openedloop concept, using a fixed 50% duty cycle. Consequently, the
scheme can be implemented using a low cost digital circuit,
which is much simpler than the closed-loop system proposed by
the authors of [12] and [30]. The latter requires microcontrollers,
current, and voltage sensors for MPPT computation. In average,
the circuit utilizes 0.5 inductor per module, compared to one per
module for topologies in [12], [14], and [38]. Since the circuit
is readily retrofitted to the PV system, no modification into the
existing central inverter is required. It can be plugged under the
module with minimal additional wirings.
It has to be noted that the idea and concept of this topology
was initially published in [8]. However, in that paper, there is insufficient detail on the analysis of the circuit operation. Furthermore, limited results are presented, i.e. the circuit performance
is illustrated by only four modules, which implies that the interconnection circuit between the different units is untested. In this
paper, an extensive analysis is carried out to describe the operation of the energy recovery circuit from shaded modules. An
experimental test rig involving eight (retrofitted) PV modules,
along with an in-house solar simulator, is constructed. Using the
solar simulator, various partial shading conditions are emulated
to verify the performance of the proposed circuit. The efficiency
of the proposed work is evaluated against the typical PV system (i.e. with the bypass diode only). It is envisaged that the
improvements mentioned previously yield a satisfactory return
of investment over the long run.
II. PROPOSED CIRCUIT
A. General Block Diagram
Fig. 1 shows the overall block diagram of the proposed circuit to harvest the power from the shaded module. The circuit
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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 29, NO. 12, DECEMBER 2014
Fig. 1 Overall block diagram of the proposed PV power generation system
retrofitted to a grid-connected PV.
Fig. 3.
Basic unit energy recovery circuit.
the process of recovering the power from the shaded module
(PV1) begins.
Fig. 2
Trigger circuit.
is connected in parallel to the original PV modules; therefore,
it can be easily retrofitted to the existing system with minimum
changes in the electrical wirings. In Fig. 1, the PV system is
a grid-connected type using one central inverter with MPPT.
However, the proposed circuit can be equally effective for standalone system, for example, using battery banks. Note that the
circuit only functions during the occurrence of partial shading.
Under the uniform irradiance, the PV system operates in the
normal way, i.e. the bypass diode is in the OFF state. During
this condition, the circuit draws minimal power, just enough to
maintain the operation of the trigger circuit.
When partial shading occurs, the trigger circuit is automatically turned ON and it activates the energy recovery circuit—
thus bypassing the bypass diode. From then on, the energy recovery circuit will start the process of recovering the power from
the shaded module, which shall be detailed in the following section. For brevity, in Fig. 1, only two PV modules are shown.
However, the system can be expanded to 4, 8, 16, 32 modules,
and so on using a simple interconnection scheme.
B. Trigger Circuit
The details of the trigger circuit are shown in Fig. 2. During
the normal operation (i.e. uniform irradiance), the proposed circuit is cut-off from the modules. Thus the PV system operates as
if the proposed circuit does not exist. However, if partial shading
occurs on PV1, for example, its associated bypass diode will be
shorted-circuited. The differential amplifier will sense the low
voltage (across the diode) and then compare it with a voltage
trigger, Vt . If a certain condition is satisfied, the comparator
enables the gate signal and thus triggers the energy recovery
circuit. Once the recovery circuit is activated, the voltage across
PV1 rises. The bypass diode is now open-circuited, and PV1 is
directly connected to the energy recovery circuit. Consequently,
C. Energy Recovery Circuit
Once the partial shading condition is detected, the energy recovery circuit is turned ON by enabling the gate drivers of the
switches. To illustrate the recovery concept, a string of four PV
modules is used as shown in Fig. 3. For simplicity, a constant
current source is used to represent the output power (when multiplied by the PV voltage) drawn from the PV system at MPP.
This is acceptable since the objective of the work is to show the
effectiveness of the circuit when dealing at the input side of the
PV system. This approach is suggested in [41] to avoid complexities in the analysis as well as the simulation. In addition,
since the bypass diode is not activated during partial shading, it
can be removed to simplify the analysis.
The basic unit of this topology comprises of four PV modules, which is divided into two groups. Group 1 involves
PV1 and PV2, together with their corresponding power electronics circuit, comprising of S1 , D1 , L1 , C1 , S2 , D2 , and C2 .
These components form what is referred to (in this paper) as
the “within group” circuit. Group 2 includes PV3, PV4 with
S3 , S4 , D3 , D4 , L2 , C3 , and C4 . In order to connect the groups
(or “intergroup”), the capacitor C5 is used. One of the main
advantages of the circuit is that the duty cycles of all switches
are fixed at 50%. So, only simple control logic is used to control
the switches.
Assuming that PV1 is shaded and PV2 receives a full irradiation, PV2 delivers higher current than PV1. However, since the
modules are connected in series, the string current will be limited to the amount delivered by PV1. That is why a bypass diode
is needed to divert the current away from PV1, or else a hot spot
is created in PV1. The main idea behind the proposed method is
that, during partial shading, part of the current from PV2 is diverted to the energy recovery circuit (by turning S2 ON) and the
energy is stored temporarily in a storage element, L1 . By doing
so, the string current can be maintained at the level generated
by PV1 and hence there is no need for PV1 to be bypassed. As
a result, PV1 is still able to actively produce power (albeit in a
RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
Fig. 4. Circuit operation within group when PV1 is shaded, while PV2 is not
shaded: (a) Mode 1 and (b) Mode 2.
lesser amount, depending on the shading condition) because its
voltage is not zero. Meanwhile, the energy stored in L1 will be
released back to the output via D1 (by turning OFF S2 ). Thus,
ideally, using this scheme, no PV power is wasted except for the
losses due to the switches, diodes, and the nonidealities of the
passive components. Note that a dead time of 400 ns is applied
during transition of the paired switches, for example, between
S1 and S2 . However, the dead time does not affect the overall
behavior of the system.
III. OPERATIONAL MODES AND ANALYSIS
A. Operation “Within-Group”
The operation of the circuit within the group can be divided
into two modes, which are defined by the states of the switches
in the circuits. During the MPP, both the PV and the load are
reacting as a constant current source. Therefore, to simplify the
analysis [39], at the MPP, the total current of both PV modules
is replaced by a constant current source (IM PPT ), as shown in
Fig. 4. Furthermore, the nonidealities of the components are
also omitted.
Mode 1 (t0 < t < t1 ): The operation of the circuit during
Mode 1 is shown in Fig. 4(a). Its corresponding timing diagram
is shown in Fig. 5. In this mode, S2 is turned ON, while S1
is turned OFF. The current flows through S2 , causing iL 1 to
increase linearly due to the constant voltage supply from PV2.
Hence, part of the energy from the nonshaded module (PV2) is
Fig. 5.
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Timing diagram for group 1 of the proposed method.
temporarily stored in L1 . This can be understood by observing
the current waveforms in trace c of Fig. 5. The ripple current of
L1 can be expressed as
∆IL 1 =
VPV 2 DT
L1
(1)
where ∆IL 1 is the ripple of the inductor current, i.e. (Im ax −
Im in ), while D and T are the duty cycle and the period of the
switching, respectively.
Mode 2 (t1 > t > t2 ): In this mode, S1 is turned ON and S2
is turned OFF, as shown in Fig. 4(b). When S2 is turned OFF,
the current is forced to flow through the freewheeling diode, D1 .
This current is shown by the trace e in the timing diagram. The
stored energy in L1 is released in the form of current and flows
to the load. Since the duty cycle of the circuit is fixed at 50%, the
average inductor current, (iL 1 ) is divided equally to form IW 1
and IW 2 . Furthermore, the ac components of IW 1 and IW 2 are
filtered by the capacitors C1 and C2 ; thus, only the dc currents
flow to the load. The load current, IPV (which is equal to the
average PV string current) at Node 1 can be written as
IPV = IPV 1 + IW 1
(2)
where IPV1 is the string current (note: IPV1 is limited by the
PV1 current). However, at Node 2, the same current can be
expressed as
IPV = IPV 2 − IW 2 .
(3)
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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 29, NO. 12, DECEMBER 2014
Since the duty cycle is 50%, it follows that
IW 2 = IW 1 =
IW
.
2
(4)
Therefore
2IPV = IPV 1 + IPV 2
IPV =
IPV 1 + IPV 2
.
2
(5)
Equation (5) indicates that the total current to the load (at
MPP) is contributed by the nonshaded module as well as the
shaded one. In another word, the proposed circuit acts as a “balancing” element to equalize the currents between the shaded
and nonshaded modules such that the current at Node 1 equals
Node 2. This implies that during the occurrence of partial shading, the energy from the shaded module is recovered and transferred to the load. Since the output current is increased, while
the voltage across the shaded voltage is near its VM P , the overall energy yield is increased. This is in contrast to the bypass
diode method, in which the energy from the shaded module is
not usable because the voltage across it is zero.
For further clarification of the concept, the numerical values
of currents are used for simulation in Fig. 5. In this case, the PV1
and PV2 currents are 2 A and 4 A, respectively. The resulting
average load current is 3 A, which is in accordance with (5).
B. Operation: “Intergroup”
When more than two groups are connected in series (to form
a unit), the intergroup connectivity is required. The intergroup
operation can be explained using Fig. 6. For clarity, capacitors
C1 , C2 , C3 , and C4 (which act as filters), and L1 and L2 are
removed because they are not involved in the intergroup interaction. Note that PGV1 is the series combination of PV1 and
PV2 after the currents of the shaded and nonshaded modules are
successfully balanced. Similarly, PGV2 is a series combination
of PV3 and PV4. For the purpose of discussion, PVG1 is designated to be the shaded group, while PVG2 is the nonshaded
one.
Mode 1 (t0 < t < t1 ): The intergroup operation during
Mode 1 is shown in Fig. 6(a). Its corresponding timing diagram
is shown in Fig. 7. In this mode, S2 and S4 are simultaneously
turned ON, while S1 and S3 are turned OFF. The current flows
through D2 and S4 , causing the capacitor C5 to be charged. Consequently, part of the energy from the nonshaded group (PVG2)
is temporarily stored in C5 .
Mode 2 (t1 > t > t2 ): In this mode, the energy previously
stored in C5 (during Mode 1) is released to the output. This is
achieved by turning ON S3 as shown in Fig. 6(b). Since the duty
cycle of S3 is 50%, IG is divided equally to form IG 1 and IG 2 .
The MPPT current, IPVG at Node 1 can be written as IPVG =
IPVG1 + IG 1 . At Node 2, the same current can be expressed
as IPVG = IPVG2 − IG2 . Using the similar analysis as in the
previous section, the average PV current that flows to the output
can be written as
IPVG =
IPVG 1 + IPVG2
.
2
(6)
Fig. 6. Circuit operation intergroup when group 1 is shaded, while group 2 is
not shaded: (a) Mode 1 and (b) Mode 2.
From (6), it can be observed that the total MPPT current is the
contribution by the nonshaded intergroup as well as the shaded
one. Effectively, the circuit provides a path for higher current
of the nonshaded group to flow so that the current from the
shaded group can be utilized. It should be noted that if a bypass
diode is used, the voltage across the shaded modules is zero;
consequently, no power can be harvested from them.
The proposed circuit that comprises of eight modules (two
units) is shown in Fig. 8. It requires additional two switches (S9
and S10 ) and an inductor (L5 ) to nestle the two units together.
The operation of this circuit is similar to the intergroup situation. However, in this case, PV1 through PV4 are considered
as one unit, while PV5 through PV8 is another unit. Using the
same intergroup concept, the connectivity can be established by
manipulating S9 and S10 in conjunction with L5 . Note that, by
this manner the number of modules can be expanded to 16, 32,
64, and so on.
RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
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TABLE I
(a) SHADING CONDITIONS FOR EIGHT MODULES. (b) STATES OF SWITCHES,
INDUCTORS, AND CAPACITORS WHEN SUBJECTED TO SHADING
CONDITIONS GIVEN IN TABLE I(a)
Fig. 7.
Fig. 8.
Timing diagram of intergroup operation of the proposed method.
Proposed circuit with eight PV modules.
Table I(b) summarizes the states of all switches and diodes, as
well as the charging and discharging of inductor and capacitors
for eight modules. Different partial shading conditions are imposed, as shown in Table I(a). To be consistent with the earlier
analysis, the modules are intergrouped and labeled as follows:
[PVG1 = PV1 + PV2], [PVG2 = PV3 + PV4], [PVG2 =
PV5 + PV6], and [PVG4 = PV7 + PV8]. In addition, the nestled intergroup is defined as: [PVBG1 = PVG1 + PVG2] and
[PVBG2 = PVG3 + PVG4]. At the output side of the circuit,
the boost converter (with P&O MPPT), the PI controller, and
the load are interconnected to emulate the IM PPT (as shown in
Fig. 6).
As an example, for shading Condition 1, only PV1 is shaded.
It receives 0.5 S (1.0 S = 1.0 kW/m2 ) while the rest of the modules are fully irradiated (at 1.0 S). During Mode 1, S2 conducts
the current and starts to charge L1 . In Mode 2, D1 is conducting, and the energy is discharged from L1 . In order to allow
for higher current from PVG2 to flow to the output, it needs
a new current path, which is provided by C9 . In this situation,
C9 allows the energy to be transferred from PVG2 to PVG1 by
storing it during Mode 1, and releasing it during Mode 2. Furthermore, it can be observed that the total irradiation of (nestled
intergroup) PVBG1 is less than PVBG2. Due to the unbalanced
irradiation, another current path is required to allow the energy
from PVBG2 to flow to the output. This path is provided by L5 ;
it is charged through S10 during Mode 1 and discharged through
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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 29, NO. 12, DECEMBER 2014
D9 in Mode 2. The operation for Conditions 2 and 3 are similar as above, but the modules are subjected to different shading
patterns. For Condition 4, the total of irradiation of PVBG1 and
PVBG2 is equal, but the shading locations are interchanged.
There is no need to provide a current path between PVBG1
and PVBG2; both S9 and S10 can be turned OFF. However in
this work, S9 and S10 are turned ON and OFF alternately, in
synchronization with S1 and S2 .
IV. EXPERIMENTAL SETUP
A. Simulation Model
The proposed energy recovery system is validated using
MATLAB-Simulink simulation as well as experimental prototype. Two sets of experiments are carried out. The first set
utilizes four PV modules, i.e. one unit. The purpose is to verify
the analysis given in Section III. The second experiment is using eight (two units) modules, as shown in Fig. 8. For the PV
simulation, the two-diode model of the solar cell is used [42]
as it gives more accurate results than the more popular single
diode model. For consistency, the same circuit is used for hardware verification. Experimentally, the BP-MSX60 PV module
is used. Its peak rated power is 60 W (3.5 A/17.1 V) at standard test conditions (STC). The original manufactured module
is modified (by rearranging its internal wiring) such that it becomes two modules (8.55 V, 30 W each). Thus the totally rated
power for the experimental rig at STC is 240 W.
B. Power Circuit
The power circuit is constructed using ten IRFB4332 PBF
MOSFETs. This device has an integrated freewheeling diode;
thus no (additional) external diode is required. The values of
inductors (L1 − L4 ) are 500 µH. These are computed by considering the allowable inductor current ripple, based on (1). The
capacitors (C1 − C4 ) are chosen to be 100 µF; the values are
derived by simulation. The PV (along with the proposed circuit)
is connected to a boost converter. The latter is equipped with the
P&O MPPT algorithm. The boost converter has the following
specifications: switching frequency, f = 40 kHz, filter capacitor,
C = 500 µH, and boost inductor, L = 500 µH. A 70-Ω resistor
is used to represent the load. Similarly, the boost converter uses
the IRFB4332PBF and BYW29EX-200 for its switch and diode,
respectively. To measure the PV voltage, VPV , a simple voltage
divider is used. Furthermore, an LEM brand current transducer,
rated at 10 A is selected for the IPV current measurement. In
addition, a low cost 16-bit Infineon XC167 microcontroller is
used to implement the MPPT algorithm. A PI controller is applied to maintain the PV voltage, VPV , at the voltage reference,
Vref . The PI controller is manually tuned such that the steady
state condition is reached in less than 20 ms.
C. Solar Simulator
In other work [6], [41], it is assumed that during partial shading, the shaded modules are considered to be 100% shaded.
This assumption, in practice, might not be accurate because,
typically, the shaded module still receives a certain amount of
Fig. 9 Circuit used to validate the concept of the proposed energy recovery
circuit.
energy. Thus, it is not sufficient just to partially shade the modules and assume it receives zero irradiance. Rather, the amount
of shading must be known so that performance of the proposed
circuit can be quantified. To create a controllable irradiance condition, an in-house solar simulator is designed and built. It is
constructed using an array of tungsten–halogen light bulbs, each
rated at 50 W. Although the application of tungsten–halogen is
not ideal [43], it has been used in other similar works, for example in [44]. The BP-MSX60 PV module (which is split into two,
with dimension of 47 in × 10 in each) is illuminated by 18 unit
of these bulbs. To avoid disturbance by a 100-Hz ripple (from
ac source), the bulbs are powered by dc sources. The irradiance
is varied by controlling the intensity of the bulbs using the dc
light dimmer circuit. At all times, the irradiance and temperature are measured using an irradiance meter and a temperature
sensor, respectively. The simulation conditions (especially the
parameters of the two-diode model) are adjusted to match the
measured irradiance and temperature when the actual readings
are taken.
V. RESULTS AND DISCUSSIONS
A. Validation of the Energy Recovery Concept
To validate the concept and analysis of the proposed energy
recovery circuit, experiment using four modules (configured as
one unit) is carried out. The case is made similar to the one
described in Section III. For ease of referencing, the circuit is
redrawn again as in Fig. 9. To ensure consistency, both validation
methods, i.e. simulation and hardware, use the same component
values and parameters. The irradiance conditions for the modules are designated as follows: PV1 = 0.3 S, PV2 = 0.3 S,
PV3 = 0.5 S, and PV4 = 0.6 S.
Fig. 10 shows the key waveforms of the simulated circuit,
while the hardware results are represented by the oscillograms
shown in Fig. 11. Note that Fig. 11 has to be divided into
subparts (a) and (b) because the oscilloscope can only display
four channels at a time. Since the irradiances for PV1 and PV2
are the same, the power generated by both modules is balanced. Therefore, during Mode 1, i.e. S1 and S3 are turned OFF
(and S2 , S4 are turned ON), the current (iL 1 ) that flows into its
corresponding storage inductor (L1 ) has an average value of
RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
6465
Fig. 10 Simulated timing diagram of circuit in Fig. 9. Trace (i): switching
signal S 1 , S 3 , trace (ii): inductor current, iL 1 , trace (iii): inductor current, iL 2 ,
trace (iv): capacitor current, iC 5 , trace (v): PV output current, IP V , and trace
(vi): PV output voltage, V P V .
zero. This fact can be observed in the simulation (trace (ii) of
Fig. 10) and verified by the hardware results of Fig. 11(a). To
relate it with the analysis in Section III, these two modules are
grouped as PVG1. On the other hand, PV3 and PV4 (group
PVG2) receive different amount of irradiances; thus each module generates different amounts of power. The energy imbalance
causes a current (iL 2 ) with an average value of approximately
280 mA to flow into L2 . This is depicted by trace (iii) in Fig. 10
and similar result is obtained from the practical circuit. Furthermore, since the energy received by PVG1 is less than PVG2,
the capacitor C5 is charged through iC 5 . This takes place during
Mode 1. During this interval, the energy is temporarily stored
in C5 . Finally, when S1 and S3 are turned ON (Mode 2), the
energy is released to the output by discharging C5 , via IPV .
This phenomena can be observed by trace (iv) of Fig. 10. The
results from simulation are closely followed by the practical
waveforms in Fig. 11(a).
B. Dynamic Response
To show the effectiveness of the proposed circuit in recovering
the power from the shaded modules, the PV system is switched
from the bypass diode (mode) to the proposed circuit (mode).
The eight modules are subjected to the following shading patterns: PV1 = 0.25 S, PV 2 = 0.25 S, PV3 = 0.5 S, PV4 = 0.7 S,
PV 5 = 1.0 S, PV6 = 1.0 S, PV7 = 1.0 S, and PV8 = 1.0 S.
The corresponding P –V curves for the bypass diode and the
proposed method are simulated and are shown as trace 1 (blue)
and trace 2 (red), respectively, in Fig. 12(a). As expected, using
Fig. 11 (a) Oscillogram from hardware of circuit in Fig. 9. Switching signal,
S 1 , S 3 (20 V/div), inductor current, iL 1 (200 mA/div), inductor current, iL 2
(200 mA/div), capacitor current, iC 5 (1 A/div). (b) Oscillogram from hardware
of circuit in Fig. 9. Switching signal, S 1 , S 3 (20 V/div), PV output current, IP V
(1 A/div), and PV output voltage, V P V (20 V/div).
the bypass diode, a multiple peak P –V curve is obtained. On
the other hand, for the proposed circuit, the curve exhibits only
a single peak because effectively, the modules are “balanced,”
i.e. as if the partial shadings have not occurred. Also, note that
this peak is much higher than the global peak of the P –V curve
with the bypass diode.
For the system with the bypass diode, it is assumed that the
P&O algorithm successfully locates the global peak at (43 V,
93 W). This point is designated as GP1 in Fig. 12(a). It has to be
noted that such condition is the best possible scenario and may
not necessarily be true as the MPPT algorithm may be trapped at
one of the local peaks. In such a case, the output power could be
much lesser. Experimentally, this point is verified by the power
trace (red) in the oscillogram of Fig. 12(b). However, in the
practical case, the achieved voltage and power is a bit lower,
i.e. 40 V and 90.5 W, respectively. The difference between the
simulated and experimental result is acceptable, considering
1) the voltage drop across the bypass diode and 2) the power
losses due to the activation of the diode. Another possible cause
for the minor discrepancies is the variation in the temperature
of the modules that has risen during the experiment.
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Fig. 13 (a) P –V curve in bypass diode mode, with the shading condition
shown in Table II. (b) Enlargement of (a).
Fig. 12. MPPT response when the PV system is switched from the bypass
diode mode to the proposed method. (a) Simulated P –V curve. (b) Experimental
results.
TABLE II
CONDITIONS FOR THE STEP CHANGE IN IRRADIANCE IN SUN (S). Note: UNIT
SUN EQUALS 1000 W/m2 AT STC
At t1 , the system is switched to the proposed circuit mode.
From the simulation in Fig. 12(a), the peak moves to a new
global point (63 V, 128 W) as pointed by P2 in the P –V curve.
Experimentally, this movement can be observed in the oscillogram shown in Fig. 12(b). The P&O begins its tracking toward
the new MPP (following the direction of the arrow) and finally
settles at (61 V, 127.3 W). Thus, from this experiment, it can
be concluded that by applying the proposed scheme, the output power is increased significantly, in this particular shading
case by 36.8 W (29%). The slow tracking time is due to the
small voltage step size of the P&O; if the step size is chosen to
be larger, the tracking speed would be faster. However, this is
achieved at the cost of larger steady state oscillation.
C. Rapid Change in Shading Patterns
Fig. 13 illustrates the response of the PV system with the bypass diode when the irradiance pattern is changed very quickly.
The shading patterns are depicted in Table II. Initially, the shading patterns for the eight modules are subjected to Condition 1 of
Table II. The corresponding P –V curve for this pattern is shown
Fig. 14. Dynamic response of the bypass diode mode with the shading condition based on curves in Fig. 13.
in trace 1 of Fig. 13(a); for this case, the curve has four peaks. It
is assumed that the PV is initially operated at a maximum point,
P1 (48.2 V, 71.6 W). Note that, P1 is not the true global peak
due to the fact that the P&O is already trapped at a local peak.
When the irradiance is changed to Condition 2, the PV system
is now characterized by trace 2. Under this condition, the curve
consists of two peaks. For clarity, the enlargement of the PV
curves is shown as an inset of Fig. 13(b). As can be observed,
the change in the shading pattern forces the operating point to
move from trace 1 to trace 2, i.e. the power drops from P1 and
hits P2 (48.2 V, 41.6 W). From this point, the P&O algorithm
starts the climbing process (to search for the peak) and finally
settles at a new peak, GP3 (41.6 V, 57.2 W).
The movements of the PV operating points are verified experimentally. The oscillogram in Fig. 14 clearly marks all the
critical points observed during the changes. By applying Condition 1 in Table II, the initial voltage and the power are found
at 48.2 V and 71.6 W, respectively. These values correspond
correctly to P1 in the P–V curves described in Fig. 10(a). At t1 ,
the shading is changed to Condition 2 (in one step, using a control switch); consequently, the operating power drops from 71.6
to 41.6 W. The voltage, however, remains constant at 48.2 V.
Again, these values agree very closely with simulation. From
here, the power starts to climb as the P&O algorithm begins its
search for the new global peak. Meanwhile, the voltage drops
accordingly, following trace 2. It finally reaches GP3 and settles to this final value in 2.5 s. Since the sampling period for
RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
6467
TABLE III
SHADING PATTERNS. Note: CONDITION 6 IS FOR BENCHMARKING PURPOSE,
i.e., NO PARTIAL SHADING IS IMPOSED
Fig. 15 (a) P –V curve for the proposed method with the shading condition
shown by Table II. (b) Dynamic response of the proposed method for the curves
in (a).
From these observations, another important feature of the
proposed method can be deduced: for the standard P&O, there
is always a possibility that the algorithm will be trapped at the
local peak. The inability to differentiate between the local and
global peaks is a well-known drawback of the P&O algorithm
[13], [17]. As such, more complicated MPPT algorithms (that
can cater for partial shading), for example [6], [13], need to be
considered. On the other hand, with the proposed technique, the
global peak will always be tracked by a standard P&O because
the multiple peaks simply do not exist. Being trapped at a local
peak is not an issue.
D. Efficiency
the MPPT controller is 100 ms, the P&O requires 25 cycles to
complete the search for the new peak, i.e. from P1 to GP3.
Fig. 15 demonstrates the performance of the proposed method
for a step change in irradiance, for the same conditions given
in Table II. The corresponding P –V curve is shown in traces
1 and 2 of Fig. 15(a), respectively. Again, note that for the
proposed method, the curve consists only of a single peak, which
is advantageous with regards to MPPT implementation. Initially,
due to Condition 1, the simulation maximum point is located
at GP1 (65 V, 117 W). This point is also correctly shown in
the oscillogram of Fig. 15(b), i.e. the oscillation is on average
at (62 V, 115 W). When the shading condition is changed to
Condition 2, the PV characteristic changes from trace 1 to trace
2; accordingly, the operating point moves from GP1 to GP2.
The latter point is 63 V, 76 W. Experimentally, the step change
in irradiance is introduced at time t1 . As can be seen from
the oscillogram in Fig. 15(a), the power drops to 74 W, while
the voltage is maintained at approximately 62 V. Furthermore,
since the proposed system does not have multiple peaks, GP2
is located directly below GP1 in the P –V curve. Consequently,
even with a large step change in irradiance, the difference in the
operating voltage between the two global peaks is very small.
As a result, the P&O is able to track GP2 very quickly, i.e.
within one to two MPPT control cycles, or 133 ms, as indicated
in Fig. 15(b).
To investigate the efficiency improvement of the proposed
method, five irradiance patterns, representing various possible
partial shading scenarios are simulated using a string of eight
modules. These patterns are arbitrarily selected and are shown
in Table III; they are labeled as Conditions 1 through 5. The
efficiencies are benchmarked to the efficiency during the absence of partial shading, i.e. Condition 6. For simplicity, four
irradiation values, i.e. 1.0, 0.7, 0.5, and 0.25 S are used to represent different levels of shading intensities (1.0 S = 1.0 kW/m2 ).
Again, the BP-MSX60 PV module is used. Each module is derated to 25 W at 35 ◦ C, giving the total power (ideal) of 200 W
for the eight modules. For the validation, the experiment using
the same simulation scenario is carried out. Furthermore, when
the system is in the bypass diode mode, a semimanual control
is applied for the MPPT algorithm to ensure that the operating
point always matches the global peak. (Note: The P&O MPPT
cannot consistently track the global peak under partial shading
condition.)
The simulation and the experimental results are shown in
Table III. For clarity, they are summarized as bar charts in
Fig. 17. The first row (PSUM ) indicates the maximum achievable power that can be generated by the eight modules if the
contribution from each module is summed individually. PSUM
also implies the true location of MPP for each module under
various shading conditions. Thus, by definition, the efficiency
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Fig. 17. Comparison of the system efficiency [as defined by (7)] of the bypass
diode and the proposed method (simulation and experimental) for selected
partial shading conditions.
Fig. 16. P –V curves generated by the proposed method and the bypass diode
method (a) under Condition 2 and (b) under Condition 4 of Table III. (Note: P o 1
is the maximum power achievable from the eight string for the bypass diode;
P o 2 is the maximum power achievable from the eight string for the proposed
method.)
of the proposed system is computed as follows [45]:
η=
Po
PSUM
(7)
where Po is the maximum output power delivered by the string,
i.e. IPV × VPV minus the converter losses, when the modules
are subjected to the shading pattern.
For the nonshading condition (Condition 6, i.e. the benchmark), the simulated PSUM is 197.2 W. Since the P&O operates
ideally, Po = PSUM . Consequently, the efficiency is 100%. Furthermore, because all modules are uniformly irradiated, neither
the bypass diode nor the proposed circuit is activated. For other
conditions (1 through 5), the efficiency varies according to the
shading pattern imposed on the modules. For example, for Condition 2, the simulated efficiencies of the bypass diode and the
proposed method are quite high (94 and 95%, respectively). This
is because their Po is close to PSUM . Alternatively, this fact can
be confirmed by plotting their corresponding P –V curves, as
shown in Fig. 16(a). As can be seen, the peak power for bypass
diode (Po1 ) is 147.2 W, while for the proposed method, the peak
power (Po2 ) is 150.9 W. In another scenario, the shading pattern
imposed by Condition 4 results in a significant loss of power for
the bypass diode (38.3 W). This causes its efficiency to drop to
75.3%. For the proposed method, the power loss is much lower
(12.9 W); hence, its efficiency remains high, i.e. 93%. These
facts can be related to the corresponding P–V curve, as shown
in Fig. 16(b). Generally, the efficiency of the proposed method
is relatively high, (i.e. above 90%), even in the case of severe
shading, for example in Condition 5. The last row of Table IV
computes the additional power that can be harvested (using the
proposed method) to be part of the output power. This is the
amount of power that is recovered from the shaded modules,
which otherwise will be wasted if the bypass diodes are activated. However, a generalized formula for the recovered power
could not be easily quantified due to its dependence on a specific shading pattern. However, from Table IV, in general, there
is a consistent trend between the simulated and the experimental
efficiencies. The agreement between the two can be further observed by the bar graphs in Fig. 17. From these correlations, two
conclusions can be suggested: 1) the concept of energy recovery
using the proposed method is verified and 2) the experimental
rig (built using the tungsten–halogen bulbs) is adequate for the
purpose of this study.
Another important point to note is that, for the bypass diode,
it is assumed that the P&O successfully locates the global peak.
In a real situation, this may not be necessarily the case. If the
P&O is trapped at one of the local peaks, Po might become much
lower and so does the efficiency. Hence, the computed efficiency
shown in Table IV is actually the best possible case achievable
for the bypass diode. On the contrary, for the proposed method,
Po is always unique because it has only one global peak.
There is another explanation why the total power that can be
extracted by the proposed method could not reach the theoretical
value of PSUM under partial shading: the low MPPT efficiency,
ηM PPT . Recall that the duty cycles of the switches are fixed at
50%. Since the circuit is opened-loop, under different irradiance,
the voltage of every module could not be regulated to VM PP .
To demonstrate this fact, a simulation is conducted using eight
modules with shading conditions as shown in Table V. The P–V
curve for every individual module is plotted in Fig. 18. As can
RAMLI AND SALAM: SIMPLE ENERGY RECOVERY SCHEME TO HARVEST THE ENERGY
6469
TABLE IV
SIMULATED AND EXPERIMENTAL RESULTS FOR SHADING PATTERNS IMPOSED ON THE BYPASS DIODE AND THE PROPOSED CIRCUIT
(SIM: SIMULATION; EXP: EXPERIMENTAL)
TABLE V
CONDITIONS TO TEST THE DIFFERENCE BETWEEN THE TRUE AND THE
OPERATING MPP
be seen, the operating point (i.e. the voltage of the PV) does
not necessary match the true MPP. For example, for PV2, the
true MPP is 17.2 V, while the operating point is only 15.38 V.
Consequently, the power is reduced from 52.77 to 50.86 W.
Similar reductions can be seen for other shading conditions.
In overall, the reduction is reflected by the MPPT efficiency,
ηM PPT . In this case, ηM PPT is 96.5%.
From this illustrative example, it is acknowledged that for
most shading conditions, the proposed circuit will yield ηM PPT
< 100. This is to be expected because a fixed duty cycle is
employed for each switch. To ensure every module operates at
its unique MPP, a closed-loop MPPT for every module must
be employed, for example as proposed in [12]. However, to
control every switch is costly because it needs additional microcontrollers, sensors, and separate dc power supplies. As the
number of modules gets larger, the complexity of the energy
recovery circuit grows considerably; consequently, the system
may no longer be practical. In addition, the individual switch
needs to be synchronized with the MPP controller of the central
inverter, thus losing its (flexible) retrofitting feature. Based on
these considerations, it is more feasible for the proposed circuit
to remain opened-loop. Despite this drawback, in most cases,
the proposed circuit is very effective and is able to recover substantial amount of energy during partial shading, as proven by
the results shown in Table IV.
VI. CONCLUSION
Fig. 18. Operating point of each individual PV module for irradiance conditions given in Table V.
A simple circuit is proposed to increase the output power
of the PV system during partial shading. The idea is to take
the current from the nonshaded module, divert it using a power
electronics circuit, and process it to become part of the output power. Consequently, the inclusion of the proposed circuit
enables the system to deliver more power compared to the conventional bypass diode method. Simulation results show marked
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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 29, NO. 12, DECEMBER 2014
improvement in the output power, especially under heavy partial shading condition. Experimental work has shown excellent
agreement with the simulation. Experimental results show that
using the scheme, the efficiency of the system can be increased
up to 32%, compared to the bypass diode method. The improvement is more significant for the case of severe shadings. The
extra power generated is expected to compensate for the cost of
the extra components in the retrofit circuit and generates profit
in the long run.
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IEEE Trans. Ind. Electron., vol. 60, no. 3, pp. 1179–1190, Mar. 2013.
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control algorithm to overcome the PV partial shading,” IEEE Trans. Power
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2009.
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model for photovoltaic modules,” Solar Energy Mater. Solar Cells, vol. 95,
pp. 586–594, 2011.
M. A. G. de Brito, L. Galotto, L. P. Sampaio, G. de Azevedo e Melo, and
C. A. Canesin, “Evaluation of the Main MPPT techniques for photovoltaic
applications,” IEEE Trans. Ind. Electron., vol. 60, no. 3, pp. 1156–1167,
Mar. 2013.
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techniques for PV systems,” J. Electromagn. Anal. Appl., vol. 3, pp. 152–
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no. 2, pp. 848–859, Feb. 2012.
Mohd. Zulkifli Ramli was born in Terengganu,
Malaysia in 1978. He received the B.Sc. and M.Eng.
degrees from the Universiti Teknologi Malaysia
(UTM), Johor Bahru, Malaysia, in 2000 and 2004,
respectively, all in electrical engineering. He is currently working toward the Ph.D. degree at UTM in
the area of photovoltaic.
He is currently a Senior Lecturer at the Universiti Teknikal Melaka, Melaka, Malaysia. His primary
research interests include the hardware design of all
power converters and their control systems.
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Zainal Salam (M’99) received the B.Sc. degree in
electronics engineering from the California State
University, Chico, CA, USA, the M.E.E. degree in
electrical engineering from the Universiti Teknologi
Malaysia (UTM), Johor Bahru, Malaysia, and the
Ph.D. degree in power electronics, from the University of Birmingham, Birmingham, U.K., in 1985,
1989, and 1997, respectively.
He has been a Lecturer for 28 years and is currently the Professor in power electronics and renewable energy at the Faculty of Electrical Engineering
UTM. He currently holds the position of Dean of Research for Energy Research
Alliance—overseeing and managing energy-related research work in the University. He is the Founder, and currently the Director, of the Inverter Quality
Control Center, UTM. This facility is responsible to test PV inverters that are to
be connected to the local utility grid. Since 2011, he has been the Editor of IEEE
TRANSACTION ON SUSTAINABLE ENERGY (an IEEE Power and Energy Society
publication). He represents the country as the expert for the International Energy
Agency (IEA) PV Power Systems Task 13 Working Group, which focuses on
the reliability and performance of the PV power system. He is the Vice-Chair
of IEEE Power Electronics, Industrial Electronics, and Industry Application
Joint Chapter, Malaysia Section (2011–2013), Organizing Chairman for the 5th
IEEE International Power Electronics and Drives Systems Conference (2005,
Kuala Lumpur), and Coorganizing Chairman for the 2nd IEEE International
Power and Electronics and Energy Conference (2008, Johor Bahru). His main
research interests include all areas of design, instrumentation, and control of
power electronics renewable energy systems.
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 3, MARCH 2013
Evaluation of the Main MPPT Techniques for
Photovoltaic Applications
Moacyr Aureliano Gomes de Brito, Luigi Galotto, Jr., Leonardo Poltronieri Sampaio,
Guilherme de Azevedo e Melo, and Carlos Alberto Canesin, Senior Member, IEEE
Abstract—This paper presents evaluations among the most
usual maximum power point tracking (MPPT) techniques, doing meaningful comparisons with respect to the amount of
energy extracted from the photovoltaic (PV) panel [tracking
factor (TF)] in relation to the available power, PV voltage ripple,
dynamic response, and use of sensors. Using MatLab/Simulink
and dSPACE platforms, a digitally controlled boost dc–dc converter was implemented and connected to an Agilent Solar Array
E4350B simulator in order to verify the analytical procedures. The
main experimental results are presented for conventional MPPT
algorithms and improved MPPT algorithms named IC based on
proportional–integral (PI) and perturb and observe based on PI.
Moreover, the dynamic response and the TF are also evaluated
using a user-friendly interface, which is capable of online program
power profiles and computes the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main
PV MPPT methods.
Index Terms—Photovoltaic (PV) energy, PV maximum power
point (MPP) tracker (MPPT) algorithms, PV power profile, PV
tracking factor (TF).
I. I NTRODUCTION
HE growing energy demand coupled with the possibility
of reduced supply of conventional fuels, evidenced by
petroleum crisis, along with growing concerns about environmental conservation, has driven research and development of
alternative energy sources that are cleaner, are renewable, and
produce little environmental impact. Among the alternative
sources, the electrical energy from photovoltaic (PV) cells is
currently regarded as a natural energy source that is more
useful, since it is free, abundant, clean, and distributed over
the Earth and participates as a primary factor of all other
processes of energy production on Earth. Moreover, in spite
of the phenomena of reflection and absorption of sunlight by
the atmosphere, it is estimated that solar energy incident on the
Earth’s surface is on the order of ten thousand times greater
than the world energy consumption. A great advantage of PV
T
Manuscript received August 24, 2011; revised December 19, 2011 and
March 12, 2012; accepted April 18, 2012. Date of publication May 7, 2012;
date of current version October 16, 2012.
M. A. G. de Brito, L. P. Sampaio, G. A. e Melo, and C. A. Canesin are
with the Power Electronics Laboratory (LEP), São Paulo State University
(UNESP), Ilha Solteira-SP 15385-000, Brazil (e-mail: moa.brito@gmail.com;
leo_sjrp@yahoo.com; guiamelo@gmail.com; canesin@dee.feis.unesp.br).
L. Galotto, Jr., is with Federal University of Mato Grosso do Sul (UFMS),
Cidade Universitária, Campo Grande 79004-970, Brazil (e-mail: lgalotto@
gmail.com).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIE.2012.2198036
Fig. 1.
PV current-versus-voltage characteristic.
cells is the reduction of carbon dioxide emissions. By the year
2030, the annual reduction rate of CO2 due to the usage of PV
cells may be around 1 Gton/year, which is equivalent to India’s
total emissions in 2004 or the emission of 300 coal plants [1].
According to experts, the energy obtained from PV cells will
become the most important alternative renewable energy source
until 2040 [2]. In this context, the concept of distributed energy
generation became a real and present technical possibility,
promoting various research works and standardizations in the
world. Despite all the advantages presented by the generation
of energy through PV cells, the efficiency of energy conversion
is currently low, and the initial cost for its implementation is still
considered high; thus, it becomes necessary to use techniques
to extract the maximum power from these panels, in order to
achieve maximum efficiency in operation. Under uniform solar
irradiation conditions, PV panels exhibits a unique operating
point where PV power is maximized. The PV power characteristic is nonlinear, as shown in Fig. 1—considering a single
PV cell, which varies with the level of solar irradiation and
temperature, which make the extraction of maximum power
a complex task, considering load variations. Thus, in order to
overcome this problem, several methods for extracting the maximum power have been proposed in the literature [3]–[21], and a
careful comparison of these methods can result in important information for the design of these systems. Therefore, this paper
aims to assess the main maximum power point (MPP) tracking
(MPPT) techniques through models in MatLab/Simulink and
experimental results, doing depth comparisons among them
with regard to the voltage ripple, start-up of the method, tracking factor (TF), and usage of sensors. It should be informed
0278-0046/$31.00 © 2012 IEEE
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
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TABLE I
E LECTRICAL PARAMETERS OF THE PV C ELL
Fig. 2.
Equivalent model of the PV panel.
that other papers related to comparisons of MPPT algorithms
can be found in the literature [22]–[26]. However, this paper
presents additional comparisons about the MPPT algorithms,
their flowcharts, more interesting experimental results, and the
improved modified MPPT proportional–integral (PI)-based IC
and perturb and observe (P&O) methods, which presented
outstanding performances because of their inherent adaptative
capabilities. Finally, experimental results with typical daily
power profile are not found in the literature for so many MPPT
methods.
II. PV PANEL M ODELING
The equivalent circuitry of a PV cell is shown in Fig. 2,
in which the simplest model can be represented by a current
source in antiparallel with a diode and the nonidealities are
represented by the insertion of the resistances Rs (series resistance) and Rp (parallel resistance).
The PV panel simulation model is based on the output current
of one PV equivalent model, and its mathematical equation is
represented by
V +I ·R
s
(1)
I = Iph − Ir · eq·(V +I·Rs )/η·k·T − 1 −
Rp
where V represents the output PV voltage of one PV panel,
Iph is the photocurrent, Ir is the saturation current, q is the
electrical charge (1.6 × 10−19 C), η is the p-n junction quality
factor, k is the Boltzmann constant (1.38 × 10−23 J/K), and T
is the temperature (in kelvins).
Equation (1) can be modified in order to present a null root
when current I approaches the real PV current. So, (1) became
(2) as a function of its own PV current
V +I ·R
q·(V +I·Rs )
s
.
(2)
f (I) = Iph − I − Ir · e η·k·T − 1 −
Rp
Current I, with a null initial value, is utilized in an iterative
process that approximates (2) of its root, being obtained by
the Newton–Rhapson method (3), which seeks the zero of the
differentiable function
xn+1 = xn −
f (xn )
.
f ′ (xn )
Thus, the derivative of (2) is presented in
q·R
Rs
s
f (I) = −1 − Ir · eq·(V +I·Rs )/η·k·T
−
.
η·k·T
Rp
(3)
Fig. 3. PV power characteristic for different irradiation levels.
Fig. 4. PV power characteristic for different temperature levels.
The model was used as a voltage source, and the integrator
represents the capacitance that stores the injected current from
the PV panel. The PV electrical parameters are presented in
Table I.
In Figs. 3 and 4, the power characteristics of the analyzed PV
cell, considering solar irradiation and temperature changes, are
shown. The curves show clearly the nonlinear characteristics,
and they are strongly influenced by climate changes.
III. M AIN MPPT T ECHNIQUES
(4)
With the aforementioned equations, an embedded function
to simulate the PV panel in MatLab/Simulink was created.
A. Fixed Duty Cycle
The fixed duty cycle represents the simplest of the methods,
and it does not require any feedback, where the load impedance
is adjusted only once for the MPP.
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B. CV Method
The constant voltage (CV) method uses empirical results,
indicating that the voltage at MPP (VMPP ) is around 70%–80%
of the PV open-circuit voltage (VOC ), for the standard atmospheric condition. Among the points of MPP (varying atmospheric conditions), the voltage at the terminals of the module
varies very little even when the intensity of solar radiation
changes, but it varies when the temperature changes. So, this
method must be used in regions where the temperature varies
very little. A positive point is that only the PV voltage is
necessary to be measured, and a simple control loop can reach
the MPP [4], [5], [21], [22].
Fig. 5.
Implementation of P&O method through MatLab/Simulink.
Fig. 6.
Implementation of IC method using PI controller.
Fig. 7.
Implementation of the beta method.
C. MPP Locus Characterization
The basic idea of this method is to find a linear relationship
between voltage and current at the MPP (MPP locus). This
relationship is the tangent line to the MPP locus curve for
the PV current in which the minimum irradiation condition
satisfies the sensitivity of the method. The equation that guides
this method is given by (5). It should be informed that the
mathematical derivation is found in [6]. As one can observe,
it is hard to obtain all the necessary parameters, and a linear
approximation is made offline with the PV panel, translating
it as an estimation method. As the MPP locus varies with
temperature, the model needs to be updated. This is done by
measuring the open-circuit voltage periodically, which means
that the interface converter must open the PV circuit, resulting
in loss of power in these instants. This MPPT method works
better for high solar irradiations [6]
η · VT
− N · Rs · IMPP + {Voc − η[V Do + VT ]}
TL =
IMPP
(5)
where N is the number of cells, IMPP is the current at MPP,
VT is the temperature voltage, and V Do is the differential
voltage [6].
D. P&O and P&O Based on PI
The P&O method operates by periodically incrementing or
decrementing the output terminal voltage of the PV cell and
comparing the power obtained in the current cycle with the
power of the previous one (performs dP/dV ). If the voltage
varies and the power increases, the control system changes
the operating point in that direction; otherwise, it changes the
operating point in the opposite direction. Once the direction
for the change of voltage is known, the voltage is varied
at a constant rate. This rate is a parameter that should be
adjusted to allow the balance between faster response and less
fluctuation in steady state [5], [7], [18], [21]–[24]. A modified
version is obtained when the steps are changed according to the
distance of the MPP, resulting in higher efficiency. This is an
excellent method to reach the MPP, and it is independent from
the PV panel/manufacturer; however, this method may suffer
from fast changes in environmental conditions. Interesting P&O
algorithm comparisons can be found in [8]. The implementation
of P&O method using Simulink is shown in Fig. 5, and the
following equation represents this method:
dP
signal
× (−kr) = d
(6)
dV
where dP/dV represents the derivative of P in relation to V ,
kr is a constant, and d is the duty cycle.
Improvements can be obtained through a digital controller,
transforming the conventional P&O into an adaptive solution
once different step sizes according to the distance of the MPP
are performed. In steady state, the operation point is not altered
unless changes in environmental conditions happen. The key
idea is to reduce to zero the dP/dV using a closed-loop control
performing the P&O based on PI.
E. IC and IC Based on PI
The IC method is based on the fact that the power slope of
the PV is null at MPP (dP/dV = 0), positive in the left, and
negative in the right, as shown in Fig. 4 [8], [9], [22]–[25]. Thus,
due to this condition, the MPP can be found in terms of the
increment in the array conductance. Using (7), it is possible to
find the IC conditions presented by (8)
dp
dv
∆i
∆v
∆i
∆v
∆i
∆v
d(v × i)
di
=i+v
=0
dv
dv
i
=−
(a)
v
i
>
(b)
v
i
<
(c)
v
=
(7)
(8)
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
Fig. 8.
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Power extracted from PV cell with the best MPPT techniques.
where (a) represents the condition at MPP, (b) represents the
condition in the left of MPP, and (c) represents the condition in
the right of MPP.
In theory, the steady-state oscillations would be eliminated
once the derivative of power with respect to voltage is null at
MPP. However, a null value of this slope hardly ever occurs
due to digital implementation resolution. Strong points are that
this method also features a modified version and does not suffer
from fast transients in environmental conditions [10], [11].
The IC method needs to monitor both the voltage and current
of the PV as P&O method. However, it is not necessary to
calculate the PV power. A contribution in the implementation
of this method can be done by adding a simple PI controller
to improve the IC method, minimizing the error between the
actual conductance and the incremental conductance, because
the compensator can be adjusted and updated according to the
system necessity. Thus, the implementation of IC method by
means of a PI controller can be visualized in Fig. 6, using
(6) and (7). Moreover, this PI controller can reduce the ripple
oscillations in steady state, minimizing the issues involving
digital resolution implementation. This method can be seen as
an adaptative solution once it presents large step sizes when
the PV is far from the MPP; then, the step sizes are reduced
according to the distance of MPP, and finally, when the MPP
is achieved, the system operation point is not changed, unless
the climate conditions are modified. The digital PI can control
directly the duty cycle (d) or the converter current (IL). With
both constraints, it is possible to find the MPP. Using IL rather
Fig. 9. Percent of energy extracted from the PV panel—TF.
than d, it makes the control more attractive once it permits that
great changes in environmental conditions can be described
as small changes in the converter current; however, if d is
the control action, great changes means big changes in the
operation point of the converter. Thus, the controller bandwidth
must be reduced in the second case.
F. Beta Method
The beta method is the approximation of the point of maximum power through the equation of an intermediate variable β,
as given in the following [12]:
IPV
(9)
− c × VPV
β = ln
VPV
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Fig. 10. Power ripple in steady state (approximately 200 Wp).
where c = (q/(η · KB · T · N s)) is a constant that depends
on the electron charge (q), the quality factor of the junction
panel (η), the Boltzmann constant (KB ), temperature (T ), and
amount of series PV cells (N s).
Moreover, as the operating conditions change, the value of
β at the optimum point remains almost constant. Thus, β can
be continuously calculated using the voltage and current of
the panel and inserted on a conventional closed loop with a
constant reference [12]. However, for optimal performance, it
is mandatory to know the PV electrical parameters, which can
reduce the attractiveness of this method. The implementation of
this method is shown in Fig. 7.
interference issues, and because of that, implementation of this
method in the converter switching frequency is not a common
option. Ripple correlation is also based on the principles of
maximum power transfer, and it uses the oscillations in power
through all pass filters to obtain the optimal point. In other
words, the high-frequency ripples in power and voltage are
captured using high-frequency filters, which are used to compute dP/dV . Then, the sign of this derivative is used in a
signal function to indicate the right region of operation, and
an integrator also ensures the MPP. Additionally, this method
presents very fast dynamics converging asymptotically to the
MPP, and it is also possible to achieve convergent speeds at a
rate similar to the switching converter frequency; however, it is
limited by the converter controller gain [15], [16].
G. System Oscillation and Ripple Correlation
The system oscillation method is based on the principle
of maximum power transfer, and it uses the oscillations to
determine the optimum point of operation. At the MPP, the
ratio of the amplitude of the oscillation to the average voltage
is constant. This method needs only to sense PV voltage, and it
can be easily implemented with only analogical circuitries [13],
[14]. Its implementation is basically characterized by the usage
of filters. For implementing system oscillation, the double grid
frequency (in the case of grid-tied converters) or the additional
low-frequency ripple can be used. However, switching frequencies must be filtered before being acquired in order to avoid
wrong switching states and an increase of electromagnetic
H. Temperature Method
Another very good option is to use a temperature method
where the shortcomings of variations in temperature, which
strictly changes the MPP, can be avoided. For this purpose,
a low-cost temperature sensor is adopted and modifies the
MPP algorithm function, maintaining the right track of MPP.
However, temperature sensing in practical implementations can
be a problematic issue due to irregular distribution of PV array
temperature, which can be avoided in small PV converters.
Moreover, the sensor may be poorly calibrated or not correctly
attached, providing wrong measurements of PV temperature.
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
1161
Fig. 11. MPPT dynamic behavior (10–200-W step change).
This method is similar to the Vcte method, and because of that,
it is simple for implementation [17], [19]–[21]. The equation
that guides the temperature method is presented in
VMPP (t) = VMPP (Tref ) + TKvoc (T − Tref )
(10)
where VMPP is the MPP voltage, T is the panel temperature
surface, TKvoc is the temperature coefficient of VMPP , and Tref
is the standard test conditions temperature.
IV. S IMULATION R ESULTS
The average model of the boost dc–dc converter was used to
simulate the load variation controlled via MatLab/Simulink and
was added a fluctuation (low-frequency ripple) in the average
model to permit system oscillation MPPT tests. All tests were
performed considering the same temperature and irradiation
steps. All algorithms were tuned for its best efficiency, i.e., step
sizes (or gains) were increased until reaching this condition;
surpassing it, TF is reduced. Fig. 8 shows the responses of some
best MPPT algorithms evaluated, where the maximum power
is highlighted in blue and the graph in red is the PV power
extracted. The simulation setup includes a boost inductor of
2.5 mH, an output capacitor of 36 µF, and a load of 50 Ω.
Table I summarizes the PV characteristics.
Aiming to compare and adjust appropriately each algorithm
according to the application, it becomes necessary to provide
performance measures that can be used as comparison criteria.
Fig. 12. Experimental arrangement—laboratory setup.
Beyond the typical measures of dynamic responses, there are
also additional metrics that are used in these cases. Because
the transmitted energy is essential for the use of PV cell as an
energy source, a very important measure is the TF, which is the
percentage of available energy that was converted. The ripple
voltage in steady state is also of vital importance, as there is a
limit of ripple so that the panel will remain effective at the MPP.
For the MPPT algorithm to reach 98% of the power extracted,
the ripple voltage at MPP should not exceed 8.5% [27].
Other factors such as ease of implementation, number of
sensors, and cost are also desirable. The TF is shown in
Fig. 9, and according to it, the P&O modified and IC modified,
IC based on PI, ripple correlation, temperature, and beta methods stand out, and the beta and IC based on PI methods can
extract the greatest amount of energy from the PV, being on the
order of 98.5% and 98.3%, respectively.
Ripple comparisons in steady state of the power extracted are
shown in Fig. 10, where beta, IC based on PI, and temperature
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 3, MARCH 2013
Fig. 13. Dynamic behavior of MPPT methods. (a) Steps (200–100 W) and (100–200 W). (b) Initialization (0–200 W). Scales: Voltage (20 V/div), current
(5 A/div), power (100 W/div), and time [(a) 20 and (b) 200 ms/div].
Fig. 14. Initialization of ripple correlation method. Scales: Power
(100 W/div), voltage (20 V/div), current (5 A/div), and time (20 ms/div).
Fig. 16.
Fig. 15. User-friendly graphical interface—unique operation point.
User-friendly graphical interface—power profile.
methods stand out for having the slightest ripple in steady state.
The MPPT methods should also be compared with respect
to their dynamic response, i.e., how they behave when the
power panel is minimal and quickly changed to the nominal
condition. Just to test, the resulting degree of power varies
instantaneously from 10 to 200 W, and it can be evaluated
using Fig. 11. According to these results, the IC based on PI,
ripple correlation, and modified IC methods stand out, and it is
the modified IC method which presents less time to reach the
steady state. This occurred once the modified IC could be tuned
to present the biggest step size when the PV was far from the
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
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Fig. 17. Experimental power extracted for the MPPT methods.
MPP. Just to highlight, the IC and P&O methods had the same
indices of quality, since they are based on the same principle of
searching for MPPT, which is dP/dV null at MPP [28].
V. E XPERIMENTAL R ESULTS
The implemented prototype and the experimental arrangement are shown in Fig. 12, being composed by oscilloscope,
solar array emulators, converter, and personal computer.
The algorithms were digitally implemented in the dSPACE
ACE1104 platform, which emulates a DSP TMS320F240 core,
and the main results are presented in this section. The irradiation and temperature steps are configurable using the Agilent
E4350B PV emulator. The boost dc–dc converter operates with
a switching frequency of 50 kHz while the control system
presents a sampling rate of 10 kHz.
It is possible to verify the beta method, CV, P&O, and
IC dynamic responses in Fig. 13. According to the dynamic
responses, the evaluated methods presented very good performances. All of them changed the PV output power in less than
20 ms when submitted to a power change (100–200 W and
vice versa). Only the CV method presented a poor initialization
time, spending 1.6 s to reach the MPP from the OFF state.
The beta method presented a good initialization time, which
is approximately 500 ms. Experimentally, the initialization of
P&O and IC methods stands out, but the on-time perturbations
represent loss of power in steady state.
Among the evaluated MPPT algorithms, ripple correlation
presented the best initialization time, i.e., time on the order
of 50 ms to reach the maximum power from zero state. This
dynamic behavior can be easily verified in Fig. 14. This method
was tuned to allow its best performance, and it stands out
because it can present a dynamic performance close to the
switching converter frequency, but being limited by the converter controllers’ gain.
In order to facilitate the experimental evaluations and
compute the TF, an acquisition management system was implemented using C++ Builder. The PC user-friendly graphical
interface can be visualized in Figs. 15 and 16. Using this system
was possible to remotely program the array emulator with a set
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 3, MARCH 2013
Fig. 18. Similar daily insulation and temperature power profiles—oscilloscope acquisition. Right waveforms suppose sun tracker use.
Fig. 19. Similar daily insulation and temperature profiles—computed TF.
of irradiation and temperature curves forming power profiles.
The communication was made via General Purpose Interface
Bus-Universal Serial Bus to exchange data from computer
and array emulator. The evaluation of extracted power can be
observed in Fig. 17, where PMAX represents the maximum
available power and PMPPT represents the energy converted.
Similar profiles of a typical daily insulation were applied,
as shown in Figs. 18 and 19, and a good response to these
profiles represent a greater gain in relation to the study of the
ability of energy extraction in the face of real conditions. It was
supposed to simulate the daily characteristics, i.e., the power
profile not the total time, from 6 A . M . to 6 P. M . Finally, Table II
summarizes the major characteristics of the analyzed MPPT
algorithms. During the experimental evaluations, the P&O
algorithm was also implemented using a digital PI controller,
performing the adaptative P&O based on PI method. Similar
to the adaptative IC, this P&O implementation presented
more interesting results regarding the higher TF and reduced
oscillations in steady state. Thus, this MPPT algorithm was also
submitted to the same daily power profile, and the results can
be seen in Figs. 18 and 19. The higher TF can be understood
once the digital controller performs bigger step sizes when
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
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TABLE II
M AJOR C HARACTERISTICS OF MPPT A LGORITHMS
PV is far from the MPP, and when it is achieved, the steps are
reduced, minimizing the losses of power in steady state.
VI. S YSTEMS U NDER PARTIAL S HADING
Most of the aforementioned MPPT methods presented very
good indices of quality in all studied aspects, being extremely
useful in the field of photovoltaics cells. Their performances are
guaranteed for the use with microinverters (single PV cell) or
with midinverters with few series connections of PV modules
(close and with the same sun inclination) in places where the
environmental conditions are uniform most of the time; that
happens in tropical places, as an example. Nevertheless, it is
not a rule for all regions and for series–parallel connections of
several PV modules. So, these algorithms must be updated to
track the global MPPT instead of the local MPPT, in the case
of shading phenomena [29]–[32]. It can be done by adding a
first stage before applying the appropriate algorithm. From the
employed ideas, the step-by-step scan of PV curve is a good
choice and dependent upon the step sizes but independent of
the PV array. The PV voltage is varied, for example, from the
open-circuit voltage until a percentage of its voltage, and the
voltage at the global MPP is saved in a memory. After finding
this point, the MPPT algorithm is performed to constantly track
the MPP. In order to reduce the quantity of steps to find the
true MPP, a current-controlled converter is used to increment
the PV power [29], or the local maxima are found before;
then, right and left steps are applied constantly to find the
global point [31]. This global MPPT search must be performed
constantly in order not to lose the global MPP. Time intervals of
10–15 min are used to perform this search. The TF reduction is
insignificant in comparison to the amount of energy that can be
harvested [29].
VII. C ONCLUSION
Currently, the usage of energy from PV panels is a reality,
and its intensive use will become extremely important in finding
solutions to energy and environmental problems very soon. In
this context, the used MPPT techniques are the most important to extract the maximum power available in PV. Among
the methods evaluated, the beta method was presented as a
good solution regarding high-quality TF, reduced and smaller
ripple voltage in steady state, good transient performance, and
medium complexity of implementation; however, it is dependent on the PV characteristics. It is noted that the modified IC,
modified P&O, IC based on PI, and P&O based on PI methods
also deserve mention as alternatives for outstanding performance, which are independent from the type/manufacturer of
the PV panel, with the IC based on PI and P&O based on PI
methods having the best TFs even in the face of more realistic
daily power profiles and also presenting very good transient
performance. However, it is not easy to perform division functions, and in this case, the digital implementation is desirable.
The idea of implementing the MPPT algorithms through
digital controllers can be applied to all methods if it were
possible to minimize error functions.
It is interesting to point out that the differences in performances among the best analyzed MPPTs are very slight, and
these algorithms must be evaluated according to each situation.
Nevertheless, this paper contributes as a good guide for choosing which algorithm should be implemented. Finally, it should
be pointed out that, in the case of cost reduction, it is interesting
to take in mind the temperature method. In the case of intensive
shading, the aforementioned algorithms are interesting choices
for the second stage of the MPP track.
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Moacyr Aureliano Gomes de Brito was born in
Andradina, Brazil, in 1982. He received the B.S.
and M.Sc. degrees in electrical engineering from the
Faculdade de Engenharia de Ilha Solteira, São Paulo
State University (UNESP), Ilha Solteira, Brazil, in
2005 and 2008, respectively, where he is currently
working toward the Ph.D. degree in the Power Electronics Laboratory, working on inverters for standalone and grid-connected applications.
His interests include ballasts for fluorescent lamps,
dimming control, digital control, dc-to-dc converters,
switching-mode power supplies, power-factor-correction techniques, DSPs and
field-programmable gate arrays, and stand-alone and grid-connected inverters
for photovoltaic applications.
Luigi Galotto, Jr. was born in São Paulo, Brazil,
on February 12, 1981. He received the B.S. degree in electrical engineering and the M.S. degree
in artificial intelligence applications, with a study
on sensor fault-tolerant operation in drive systems
from the Federal University of Mato Grosso do Sul
(UFMS), Campo Grande, Brazil, in 2003 and 2006,
respectively. He received the Ph.D. degree in power
electronics at São Paulo State University (UNESP),
Ilha Solteira, Brazil, in 2012.
He is also a Researcher at an acknowledged laboratory at UFMS, developing projects in spectrum analyzers, power converters,
condition monitoring software, and control systems.
Leonardo Poltronieri Sampaio was born in São
José do Rio Preto, Brazil, in 1983. He received
the B.Sc. and M.Sc. degrees in electrical engineering from São Paulo State University (UNESP), Ilha
Solteira, Brazil, in 2008 and 2010, respectively,
where he is currently working toward the Ph.D.
degree in electrical engineering.
Since 2000, he has been working on computer
programming and Linux operational systems, and
he is a member of the Power Electronics Laboratory (LEP), São Paulo State University. His interests
include computer programming, education in power electronics, e-learning,
education tools, dc–dc converters, inverters, renewable and alternative energy
sources, photovoltaic systems, and power electronic converters.
DE BRITO et al.: EVALUATION OF THE MAIN MPPT TECHNIQUES FOR PHOTOVOLTAIC APPLICATIONS
Guilherme de Azevedo e Melo received the
B.S., M.S., and Ph.D. degrees in electrical engineering from the Faculdade de Engenharia de
Ilha Solteira (FEIS), São Paulo State University
(UNESP) Ilha Solteira, Brazil, in 2001, 2006, and
2010, respectively.
Since 2010, he has been a Collaborator Professor
with FEIS, UNESP, where he is currently a Member
of the Power Electronics Laboratory (LEP).
Dr. Melo’s principal interest areas are power electronics, electrical power quality, renewable energy,
and control systems.
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Carlos Alberto Canesin (S’87–M’97–SM’08) received the B.Sc. degree in electrical engineering
from the Faculdade de Engenharia de Ilha Solteira
(FEIS), São Paulo State University (UNESP), Ilha
Solteira, Brazil, in 1984 and the M.Sc. and Ph.D.
degrees in electrical engineering from the Power
Electronics Institute, Federal University of Santa
Catarina, Florianópolis, Brazil, in 1990 and 1996,
respectively.
He started the Power Electronics Laboratory
(LEP), FEIS, UNESP, where he is currently a Full
Ph.D. Professor. He was the Editor-in-Chief of the Brazilian Journal of
Power Electronics (in 2003–2004). His interests include power-quality analysis
and techniques, active-power-factor-correction techniques, high-power-factor
rectifiers, soft-switching techniques, dc-to-dc converters, dc-to-ac converters,
switching-mode power supplies, solar/photovoltaic energy applications, electronic fluorescent ballasts, and educational research in power electronics
Dr. Canesin was the President of the Brazilian Power Electronics Society (in
November 2004–October 2006). Since 2003, he has been an Associate Editor of
the IEEE T RANSACTIONS ON P OWER E LECTRONICS, and since 2010, he has
been a member of The State of São Paulo Council for Energy Policy (CEPE).