A novel MPPT Tactic with fast convergence speed .pdf

A Novel MPPT Tactic for PV Systems with Fast-
Converging Speed and Zero Oscillation
CHELLAKHI Abdelkhalek
Chouaib Doukkali University, National
School of Applied Sciences, LabSIPE
El jadida, Morroco
chellakhi.a@ucd.ac.ma
EL BEID Said
Cadi Ayyad University, CISIEV
Marrakech, Morroco
elbeid.s@ucd.ac.ma
ABOUELMAHJOUB Younes
Chouaib Doukkali University, National
School of Applied Sciences, LabSIPE
El jadida, Morroco
abouelmahjoub.y@ucd.ac.ma
Abstract— This paper proposes a novel algorithm for
maximum power point tracking (MPPT) in photovoltaic panel
sourced boost converter. The novel MPPT tactic has a high
convergence speed and zero oscillation around the MPP under
steady state operation, and high tracking speed in response to
rapid changing of irradiance. Furthermore, it improves the
tracking accuracy, without increase the implementation
complexity. The proposed technique has been simulated in
Matlab/Simulink environment and compared with some other
MPPT techniques, such as Perturbed and observed (P&O),
Increment of Conductance (INC) and fuzzy logic (FLC).
Keywords— MPPT, boost converter, PV system, zero
oscillation, steady state.
I. INTRODUCTION
Renewable energy is an energy that can be harvested from
natural renewable resources and it is endless, sustainable and
abundant compared to human lifespan. For example, solar
energy can be harvested by converting its solar irradiance into
either heat or electricity depending on the technology used.
Wind, hydropower, tide, biomass, geothermal are also
different examples of renewable resources. Renewable
energies have enormous potential globally due to many
concerns and factors. They pollute less than fossil fuels, exist
almost everywhere and could have higher total efficiency as
the energy harvesting and conversion technologies getting
improved. Also, the global growing demand and the rise of
smart grid concept push more on selecting those sources rather
than traditional ones [1].
Recently, renewable energy resources, especially solar
energy resource, have attracted considerable attention [2]. Due
to it is many advantages like being clean energy source,
supplied by nature and producing electrical energy anywhere
there is sunlight [3], where photovoltaic (PV) generators can
either be tied to grid (operate in electric distribution systems)
or can operate in autonomous systems, e.g., battery charging,
domestic electric supply and pumping systems [4]. In the other
hand, PV generators suffer from a relatively low conversion
efficiency, which lies in the range 15 –20% [5, 6]and the
power of PV panels are affected by variable environment
conditions such as (temperature and irradiance). Which cause
a change current, voltage and maximum power point of PV
panels. To increase efficiency and decrease the cost of PV
system, it is needed to operate PV panels at MPP (Maximum
Power Point) [7].
Many MPPT algorithms were in the literature proposed as
well as: Perturb & Observe [8, 9], Inc. Conductance(INC) [10,
11], Fuzzy Logic (FLC) [12, 13], and hill climbing (HC) [4,
14] etc.
These algorithms are intended to meet different
requirement in terms, such as convergence speed, cost,
accuracy, sensors used, analogue or digital implementation
etc.
The P&O and HC are the most generally used algorithms
in partial PV power system. Nevertheless, these methods have
four major drawbacks: i slowing tracking speed at rapid
weather change. ii The oscillation around the MPP of PV
output power cannot reduced, which consequently waste the
energy from PV array. iii They fail to track MPP when the
radiation varies quickly. iv They cannot compare the array
terminal voltage with the actual MPP voltage, and which
cannot track the actual MPP at that time [15]. The INC is
requires two sensors for the measurement of V, I and lends
itself well to DSP and microcontroller control. Good
performance has many advantages such as no oscillation
occurs around the MPP in steady state [16]. However, it has
three major drawbacks: (1) the design of controller is
complicated, high cost, and need accurately measure
parameters. (2) Slowing tracking speed at rapid weather
change. (3) It fails to track MPP under the radiation varies
quickly or partial shading conditions [15].
The FLC MPPT method has an excellent performance at
varying weather and shows better tracking performance than
the P&O or HC controller [17].The main advantages of this
method is the rapid tracking speed, the ease of
implementation, few measured parameters, etc. The
disadvantages of the FLC method, is that the tracking
performance and output efficiency are highly dependent on
the engineer's technical knowledge, and the operating duty
cycle moves away from the duty cycle of actual MPP no
matter the radiation changes or the steady state, since the slope
change is less than the designed value, and the duty cycle
variation is neglected by computing the slope and comparing
with the rule-based table [15].
In this paper, a novel MPPT algorithm is presented to
surmount the mean drawback at many MPPT methods, such
as the convergence speed and the oscillation around to MPP
at steady state operation. Furthermore, the new MPPT tactic
has a good performance to track MPP with zero oscillation and
a high convergence speed, also this algorithm is expected to
reduce the power loss and improve the response speed of
tracking.
2020 5th International Conference on Renewable Energies for Developing Countries (REDEC)
978-1-7281-5595-1/20/$31.00 ©2020 IEEE
Authorized licensed use limited to: Cornell University Library. Downloaded on August 15,2020 at 09:10:13 UTC from IEEE Xplore. Restrictions apply.

The mean idea of the proposed method is that the zone of
MPP for different level of irradiance at a constant temperature
is limited to a small interval (zone of MPP) as shown Fig. 1
and Fig .2.
Simulation results are provided to evaluate the
effectiveness and robustness of the proposed MPPT tactic.
The remaining of the papers is as follows; Section II illustrates
the model and characteristic analysis of PV system. Section
III presents the novel MPPT tactic. Next, the simulation and
results are described in section IV. Finally, the conclusion of
the study are reported in section V.
Fig. 1. P-V characteristic of PV panel for MPPT algorithm.
Fig. 2. I-V characteristic of PV panel for MPPT algorithm.
II. MODEL AND CHARACTERISTICS ANALYSIS OF PV SYSTEM
This section is divided into two subsections. Section A will
introduce the equivalent circuit and characteristics of a
photovoltaic module. Moreover, section B will present the
DC-DC converter.
A. Photovoltaic module
The PV module consists of numerous solar power cells.
The latter, also known as a PV cell, is the unit component of
the PV panel.
Equivalent circuit of a PV cell is shown in Fig. 3. There
are two resistances and a diode. The parallel RP resistance
represents the loss which small leakage current flow through
the parallel path (High value order of 𝑘Ω), RS (about 1Ω)
represents the losses which are loss of metal grid, contacts and
current collecting bus, diode represent a cross current which
associated with p-n junction, semiconductor devices [7, 18].
According to the equivalent circuit shown in Fig. 3, the
mathematical expression of the PV panel output current Ipv
can be written as:
Ipv= nP×IG-nP×I0
(exp (
q×(Vout+Iout×RS)
A×K×T×nS
) -1) -
nP×
(Vout+Iout×RS)
nS×RP
(1)
Fig. 3. Equivalent circuit of solar cell.
Where, Ipv is the cell output current, IG is the current of
photovoltaic array, 𝐼0 represents the PV array reverse
saturated current, 𝑛𝑃 and 𝑛𝑆 are the numbers of solar power
cells in parallel and in series, respectively. q Is the electronic
charge value (1.6×10-19
C), Vpv is the cell output voltage, A is
dimensionless junction material factor, k is Boltzmann's
constant (8.65 × 10−5
𝑒𝑉/𝐾) and 𝑇 is the temperature of the
p-n junction (𝐾) [12].
As can be seen from the equation, the PV output current
shows a nonlinear characteristic.
B. DC-DC Boost Converter
Among DC-DC converters typically employed for
generating solar power, DC-DC boost showed in Fig. 4 is the
most popular one, which is ensure less loss of energy when
transferred between the PV panel and the load by modifying
the duty cycle which affects the operating point of the PV
module [7, 19].
Fig. 4. Boost converter.
The MPP tracker regulates the duty ratio of the DC-DC
converter in order to match source and load impedances
aiming at delivering maximum power to the load. Boost
converter is used in this study, due to its higher conversion
efficiency, simplicity and high reliability with respect to other
more complex configurations [4].
The switching device used in this converter is a MOSFET,
which is faster than an IGBT, with less power losses at high
frequencies. The MOSFET is controlled by PWM (Pulse
RL
RP
RS
IG
I0
PV Cell
Vpv
Ipv

Width Modulation) [19], influencing the duty cycle, the
relationship between the input voltage 𝑉
𝑝𝑣 and output voltage
𝑉𝑜𝑢𝑡 is given by:
Vout=Vpv
1
1-d
(2)
Iout=Ipv(1-d) (3)
Dividing (2) by (3), leads to:
Rout=
Vout
Iout
=
1
(1-d)2 ×
Vpv
Ipv
=
1
(1-d)2 ×Rin (4)
Where 𝑅𝑖𝑛 and 𝑅𝑜𝑢𝑡 refer to the input and output
resistance respectively. In a PV system, (4) can be rewritten
as:
Rload =
Rpv
(1-d)2 (5)
Where 𝑅𝑙𝑜𝑎𝑑 refers to the load resistance, and 𝑅𝑝𝑣 refers
to the resistance seen by the PV string.
According to (5), the duty cycle of the boost converter can
be obtained as :
d=1-√
Rpv
RLoad
(6)
III. THE NOVEL MPPT TACTIC
This novel MPPT method is given to overcome a most
drawbacks, which suffer from several MPPT algorithms. The
principle of this algorithm is very easy it is illustrated in Fig.
1 and Fig. 2, where you can see that the zone of MPPs and
zone of 𝑉
𝑚𝑝𝑝𝑠 are located in smaller region, were the latter is
limited by Vmppmin
and Vmppmax
.
Firstly, the voltage and current of PV panel are measured,
so the 𝑉(𝑘) is compared with Vmppmin
and Vmppmax
, if 𝑉(𝑘) is
greater than Vmppmax
it receives the value of Vmppmax
, and if
the 𝑉(𝑘) is less than Vmppmin
, it receives the value of Vmppmin
.
When the voltage is regulated, the below relation (7) is used
for calculated the new duty cycle of the boost converter which
its follows as:
d(k+1)=1-√
V(k)/I(k)
RLoad
(7)
Moreover, if 𝑉(𝑘) is within the range
(Vmppmin
to Vmppmax
), the new duty cycle 𝑑(𝑘 + 1) receives
the last duty cycle 𝑑(𝑘).
The flowchart of this novel MPPT tactic is showed in Fig.
6, where is clear that our algorithm has a direct control
strategies to seeks MPP by sensing the voltage and the current
of the PV panel, furthermore, it requires less sensors and has
few complexity in hardware implementation (circuit
complexity).
Fig. 5 illustrates the 𝑃𝑝𝑣 – 𝑉
𝑝𝑣 characteristic curves of the
PV module under four levels of irradiance, with
corresponding MPPs at points A, B, C, and D. When the
irradiance level rapidly increases, the characteristic curve
changes from Curve 1 to Curve 2,to Curve 3 and then to
Curve 4. During this process, the proposed algorithm operates
consistently at the MPP. Therefore, the actuating points are
located at points A, B, C and D respectively for Curve 1,
Curve 2, Curve 3 and Curve 4. Consequently, the proposed
algorithm is suitable for application under various irradiance
conditions and has a high reliability.
Fig. 5. 𝑃𝑝𝑣 – 𝑉
𝑝𝑣 Characteristic curve of the PV module under rapidly
changing irradiance.
Fig. 6. Flowchart of novel MPPT tactic.
IV. SIMULATION AND RESULTS
In order to demonstrate the efficiency of our approach the
performance of the novel MPPT technique is studied for
various environmental conditions. The implementation is
simulated numerically using Matlab/Simulink software
(R2018a), with resistive load (R = 10 Ω). The specifications
of the PV module are listed in Table 1, and the parameters of
boost converter are as follows: Cin=470 uF, Cout=47 uF and
L=1mH. The switching frequency for the MOSFET is set to
10 kHz.
𝒅(𝒌 + 𝟏) = 𝟏 − √
𝑽(𝒌)/𝑰(𝒌)
𝑹𝒍𝒐𝒂𝒅
No Yes
Yes V(k)<
Vmppmin
V(k)>
Vmppmax
Start
V(k)=Vmppmax
V(k)=V(k)
V(k)=Vmppmin
Update d(k+1)
Yes
No
d(k+1)=d(k)
Measure
V(k), I(k)
𝑽(k)<Vmpp
min
Or V(k)>Vmpp
max
?

A. Irradiation Variation under Strong Intensity
In this simulation, Fig. 7 shows a comparison between the
novel MPPT technique and different MPPT techniques such
as the famous P&O, INC and the fuzzy logic in [7]. In this
test, the temperature was constant at 25°C, and irradiation
was varying under different levels as shown in Fig. 8.
It is clear by the zoomed portion (1), (2) and (3) of Fig. 9
that the proposed MPPT technique tracks the maximum
power faster and with zero oscillation compared to P&O and
INC algorithm, which have larger steady state oscillations.
The FLC method has fast convergence speed, but it can note
attaint the MPP and it has a bad tracking in low irradiance
levels.
Furthermore, the novel MPPT operated consistently at the
MPP in many level of irradiance, but it is clear that other
MPPTs method can note track the MPP and they are too far
from it in low irradiation levels.
Fig. 7. PV output power characteristic for the simulation results.
Fig. 8. The Irradiation variation profile.
Zoom 1.
Zoom 2.
Zoom 3.
Figure 9. Zoomed portion 1, 2 and 3.
Fig. 10. The simulation results for the PV: (a) Current. (b) Voltage output,
(c) the Duty cycle of boost converter.
Table 1. Parameter of the 1Soltech 1STH-215-P PV module at STC:
Temperature = 25oC, Insolation = 1000W/m².
Parameters Value
Maximum power (Pmpp)
Voltage at MPP (Vmpp)
Current at MPP (Impp)
Open Circuit Voltage (Voc)
Short Circuit Current (Isc)
Temperature coefficient of Voc
Temperature coefficient of Isc
212.93 W
29 V
7.35 A
36.3 V
7.84 A
-0.36099 (%/°C)
0.102 (%/°C)

Fig. 11. Simulation result of output PV power.
Fig. 12. The Irradiation variation profile.
Fig. 13. The load variation profile.
Fig. 14. Duty cycle output.
Fig. 10 shows the simulation result of the PV current and
voltage output, and the duty cycle of boost converter, it can
be noticed that the voltage, the current and duty cycle of the
proposed tactic are stable and have not oscillation in the study
state operation. Contrary to P&O and INC methods, which
have three-level oscillations as can be observed in Fig.10,
which results in extra power losses.
Another simulation results are shown in Fig. 11 for
different irradiation levels is showed in Fig. 12, in order to
examine the performance of novel MPPT tactic. It is clear
from Fig.11 that is the proposed algorithm has high accuracy
to fetch the MPP with less time convergence, and zero
oscillation around the MPP.
B. Load variation
Fig. 15 shows the simulation results for a load variation
from 10 Ω  30 Ω  20Ω at t = 0.03s, 0.06s respectively,
this scenario is shown in Fig. 13. During this period, the
irradiance level and temperature are kept constant at
1000W/m² and 25°C respectively.
The simulation results for the load variation scenario are
similar to those obtained in the previous. The novel method is
the fastest method to locate the MPP while the P&O method
is the slowest one.
As shown in the power waveforms in Fig. 15, the
proposed algorithm has high tracking speed. Initially, the
MPP is tracked at t = 0.007 s for the novel MPPT, but in the
INC and P&O the MPPT algorithm are tracked at 0.013 s and
0.015 s respectively.
The FLC MPPT technique loses the tracking direction, as
the load changes are not taken into consideration in its
training process. Thus, its duty ratio (showed in Fig. 14) has
not changed but remains fixed as the radiation level is fixed.
However, the P&O and INC MPPT techniques succeed in
following the MPP locus, but with high steady state error and
a large deviation when the variation load is detected, as
observed in the zoomed portions of Fig. 15. On the other side,
the proposed MPPT technique tracks the power locus almost
perfectly with zero steady state error, specifically when the
variation load is detected.
V. CONCLUSION
This paper proposed a novel MPPT tactic for PV system.
The proposed algorithm can more improve the tracking
accuracy and eliminate the oscillation around the MPP in
steady state operation. The implementation system only
requires a DC-DC converter and PIC or Arduino, which is

simpler than other MPPT algorithms, which requires extra
control loop and intermittent disconnection. Furthermore, the
novel algorithm responds to the sadden variation in solar
irradiation and load faster variation compared the other
conventional algorithms as shown in the simulation results.
In addition, there is no steady state oscillation in the proposed
algorithm which thus reduce the power losses. A simulation
evaluation demonstrates the superior performance over
traditional MPPT methods.
In this paper, we only adopt a demonstration with
simulation in order to prove the ability of the new MPPT
algorithm. An experimental implementation will be added to
validate the proposed MPPT tactic under real values of
irradiation in some Moroccan cities.
Fig. 15. PV output power for load variation.
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