Improved Performance Low-Cost Incremental Conductance PV MPPT Technique
N.E. Zakzouk, M.A.Elsaharty, A.K. Abdelsalam, A.A. Helal
B.W. Williams
Electrical and Control Engineering Department Electronics and Electrical Engineering Department
Arab Academy for Science and Technology (AAST) Strathclyde University
Alexandria, Egypt Glasgow, United Kingdom
Abstract-Variable-step incremental conductance (Inc.Cond.) technique, for photovoltaic (PV) maximum power point
tracking (MPPT), has merits of good tracking accuracy and fast convergence speed. Yet, it lacks simplicity in its
implementation due to the mathematical division computations involved in its algorithm structure. Furthermore, the
conventional variable step-size, based on the division of the PV module power change by the PV voltage change, encounters
steady-state power oscillations and dynamic problems especially under sudden environmental changes. In this paper, an
enhancement is introduced to Inc.Cond. algorithm in order to entirely eliminate the division calculations involved in its
structure. Hence, algorithm implementation complexity is minimized enabling the utilization of low-cost microcontrollers to
cut down system cost. Moreover, the required real processing time is reduced, thus sampling rate can be improved to fasten
system response during sudden changes. Regarding the applied step-size, a modified variable-step size, which depends solely
on PV power, is proposed. The latter achieves enhanced transient performance with minimal steady-state power oscillations
around the MPP even under partial shading. For proposed technique's validation, simulation work is carried out and an
experimental set up is implemented in which ARDUINO Uno board, based on low-cost Atmega328 microcontroller, is
employed.
Keywords—PV module, MPPT, incremental conductance, variable step size, environmental changes, low-cost microcontroller, and partial
shading.
I. Introduction
The modern industrial society, population growth, and the interest in the environmental issues have greatly increased the need
of new and clean renewable energy sources [1]. Among the latter, Photovoltaic (PV) solar energy has become nowadays a real
promising renewable/ alternate energy source due to its several advantages such as; absence of noise or mechanical moving parts,
low operation cost, no emission of CO
2
or other harmful gases, flexibility in size, and its convenience with stand-alone systems in
addition to grid-connected ones where they can be installed close to load centres, saving transmission lines losses [2-3]. Although
PV energy has recently received considerable attention, high installation cost and low conversion efficiency of PV systems set a
difficulty against its use on a large scale [4]. Furthermore, the non-linear behaviour and dependency of PV panels on the atmospheric
temperature and irradiance level create one of the main challenges facing the PV sector’s penetration to the energy market [5]. To
minimize these drawbacks, PV operation at the maximum power point is a necessity which in turn maximizes the PV system
efficiency. Various MPPT techniques have been presented in literature [6-9].They differ in the tracking accuracy, convergence
speed, dynamic response under sudden environmental changes, required sensors, hardware implementation, and dependency on PV
module parameters.
The most commonly used MPPT algorithms are perturb and observe (P&O) and incremental conductance (Inc.Cond.) methods
[10]. P&O algorithm is widely used in PV stand-alone systems for its simple implementation [11-14]. In these PV systems, MPPT
algorithms are preferably realized using low cost microcontrollers in order to cut down the entire system cost. Thus, the P&O, being
an arithmetic-division-free algorithm, is a convenient choice to be implemented by these controllers. On the other hand, Inc.Cond. is
more complex in structure than P&O as it inhibits many mathematical divisions which increase the computational burden [15].
However, regarding these techniques performance, P&O can easily lead to erroneous judgment and oscillation around the maximum
power point (MPP) which results in power loss [16]. Hence, Inc.Cond. technique is a better candidate especially during rapidly varying
environmental conditions. This is because, when compared to P&O method, Inc.Cond. can accurately track the MPP, with less steady-
state oscillations and faster response during changes thus increasing the tracking efficiency [17-21].
In addition, many modifications have been introduced to fixed step-size used in the Inc.Cond. method to change it to a variable
one that gets smaller towards the MPP [22-28]. The latter improves the technique performance and solves the trade-off between
tracking accuracy and convergence speed. However, conventional variable step-size, automatically adjusted according to the PV
power change with respect to PV voltage change (∆P/∆V), can affect the MPPT performance due to the digression of this step size,
particularly under sudden changes [29, 30].
This paper aims at combining the advantages of simple algorithm structure with high system performance during transients in one
MPPT technique. Hence, a modified Inc.Cond. algorithm is proposed featuring full elimination of the division calculations thus,
simplifying the algorithm structure. In addition, a variable step-size is proposed which only depends on the PV power change (∆P),
thus eliminating its division by the PV voltage change (∆V). The proposed step-size can minimize power oscillations around the MPP
and effectively improve the MPPT dynamics during sudden changes. This will result in a total division-free variable-step technique
which does not only have the merits of enhanced steady-state and transient performance but also has simple algorithm implementation.
This reduces the processing real-time, enabling the algorithm to be implemented by low-cost microcontrollers which in turn reduces
system costs.
This paper is organized in eight sections. Following the introduction, the investigated PV system is presented. The following two
sections explain the conventional and the proposed Inc.Cond. techniques regarding their algorithm structure and the applied variable
step-size. The simulation and experimental results, which verify the superiority of the proposed technique over the conventional one,
are illustrated in the fifth and sixth sections respectively. An assessment is performed for the proposed MPPT technique under partial
shading conditions in the seventh section. Finally, a conclusion is presented in the eighth section.
II. PV system under investigation
The considered PV system consists of a PV module, a DC-DC boost converter and a battery load as shown in fig. 1(a).
Duty cycle
PV module
Boost converter
Battery
load
V
I
25 C
MPPT
Algorithm
C
PV
L
C
o
V
battery
+
-
V
+
-
Irradiance
I
pv
I
d
R
s
R
p
I
V
+
-
Ideal PV cell
Practical PV cell
(a) (b)
I
SC
I
MPP
V
OC
V
MPP
Power (W), Current (A)
I
-
V
P
-
V
(
CC
)
MPP
(
CV
)
Voltage (V)
dP
/
dV
<0
dP
/
dV
>0
dP
/
dV
=0
(c)
0 5 10 15 20 25
0
50
100
150
Power (W)
Voltage (V)
Current (A)
0
5
10
15
P-V
I-V
25 C
40 C
15 C
0 5 10 15 20 25
Voltage (V)
0
50
100
150
Power (W)
Current (A)
0
5
10
15
P-V
I-V
1000 W/m
2
700 W/m
2
400 W/m
2
(d) (e)
Fig. 1: PV system under consideration (a) Schematic diagram, (b) PV cell single diode model, (c) I-V and P-V characteristics at
given conditions, I-V and P-V curves of KD135SX_UPU PV module: (d) under three irradiance levels at 25C and (e) for three
different cell temperatures at irradiance of 1000 W/m
2
A. PV mathematical model
A practical PV device can be represented by a light-generated current source and a diode altogether with internal shunt and series
resistances as shown in fig. 1(b). A PV module is composed of several PV cells and the observation of the characteristics at its
terminals results in expressing its output current by the following equation [31];
(1) 1exp
p
s
t
s
opv
R
IRV
aV
IRV
III
where V and I are the PV output voltage and current respectively. I
pv
is the photovoltaic current which is generated by the incident
light (directly proportional to the sun irradiance) and I
o
is the saturation current of the PV module. a is the diode ideality constant
and R
s
, R
p
are the internal series and parallel resistances of the module respectively. Finally, V
t
is the PV thermal voltage with N
s
PV
cells connected in series. V
t
equals to N
s
.
k
.
T/q where; q is the electron charge (1.60217646 × 10
−19
C), k is Boltzmann constant
(1.3806503 × 10−23 J/ K), and T (in K) is the temperature of the p–n junction.
B. Boost converter
The design of boost converter, shown in fig. 1, can be summarized as follows [32];
)1( DVV
battery
(2)
sw
L
Lf
VD
i
(3)
where V is the PV output voltage, V
battery
is the battery load voltage and D is the duty ratio determined by the applied MPPT algorithm
to directly control the boost chopper switching. ∆i
L
is the change in inductor current, L is the chopper inductor and f
sw
is the chopper
switching frequency.
C. MPPT
Equation (1) shows that a PV module has non-linear I-V characteristics that depend on the irradiance level and PV cells'
temperature. Fig. 1(c) shows the I-V and P-V curves of a PV module, at a given cell temperature and irradiance level, on which it's
noticeable that the PV panel has an optimal operating point, the maximum power point (MPP). In the region left to the MPP, the PV
current is almost constant and the PV module can be approximated as a constant current (CC) source. On the other hand, right to the
MPP, the PV current begins a sharp decline and the PV module can be approximated as a constant voltage (CV) source. The PV
module characteristic curves vary with the changing irradiance level and cell temperature [5], as shown in fig. 1 parts (d) and (e).
The PV module short-circuit current is linearly dependent on the irradiance level unlike the open-circuit voltage which almost
independent of it. On the other hand, PV cell temperature significantly affects the open-circuit voltage value whereas it has a
negligible effect on the short circuit current value.
As the PV module characteristic curve shifts with changing irradiance or cell temperature, the MPP moves. Hence, continuous
tracking to the MPP becomes mandatory to maximize the PV system efficiency. The latter is achieved using an MPPT algorithm
which determines the appropriate duty ratio (D) that controls the switching of the DC-DC converter placed between the PV module
and the load to ensure that the PV panel maximum power is extracted. A successful MPPT technique compromises between the
tracking speed and steady-state accuracy and shows fast response during sudden environmental changes. According to these criteria,
the Inc.Cond. technique can be considered as an appropriate candidate [17-21].
III. Conventional variable-step incremental conductance technique
The structure of the conventional variable-step Inc.Cond. technique can be illustrated in the following two subsections;
A. Conventional Inc.Cond. algorithm
Inc.Cond. technique is based on the slope of the PV module P-V curve [6] where;
∆I/∆V=-I/V
∆V=0
Inputs: V(k), I(k)
∆I=I(k)-I(k-1)
∆V=V(k)-V(k-1)
∆I/∆V>-I/V
∆I=0
∆I>0
D(k)=
D(k-1)+∆D
I(k-1)=I(k)
V(k-1)=V(k)
Return
Yes
Yes
Yes
Yes
Yes
No No
No
No
No
D(k)=
D(k-1)-∆D
D(k)=
D(k-1)-∆D
D(k)=
D(k-1)+∆D
Fig. 2: Inc.Cond. algorithm flowchart (a) conventional
(4) MPPat 0
dV
dP
(5) MPP left to 0
dV
dP
(6) MPP right to 0
dV
dP
Since
(7)
)(
V
I
VI
dV
dI
VI
dV
IVd
dV
dP
Then
(8) MPPat
V
-I
V
I
(9) MPP left to
V
-I
V
I
(10) MPP right to
V
-I
V
I
