Page 115 - Renewable Energy Devices and System with Simulations in MATLAB and ANSYS

102 Renewable Energy Devices and Systems with Simulations in MATLAB and ANSYS ®
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are combined through the corresponding membership functions into a numerical value (defuzzi-
fication stage), thus producing the duty cycle of the control signal driving the power converter
such that the MPP is tracked. The fuzzy logic controllers have the advantage of not requiring
knowledge of the exact model of the system under control. However, in order to obtain an effec-
tive performance, expert knowledge is required for forming the membership functions and rule
sets. Thus, optimization algorithms such as genetic algorithms (GAs) and ant colony optimization
have been applied for tuning the operational parameters of fuzzy logic controllers [42], while in
[40] the structure of an ANN is exploited for that purpose.

5.3.6 Single-Sensor MPPT
The implementation of P&O and InC methods requires measurement of the PV module/array out-
put current. The accuracy of current measurements is affected by the current sensor bandwidth and
switching ripple imposed on the PV source output current due to the switching operation of the
power converter. Additionally, the use of a current sensor increases the cost and power consumption
of the MPPT control unit.
As analyzed in [43], the output power of the PV module/array is given by

P pv = V pv ⋅ I pv = V pv ⋅ V pv =⋅ 2 (5.10)
kV pv
R in

where R in is the input resistance of the power converter, which is a function of the duty cycle of the
control signal driving the power converter, and k = 1 .
R in
The value of V pv in (5.10) also depends on R in . Thus, by modifying the control-signal duty cycle,
this will affect the resulting operating values of both V pv and P pv . The power produced by the PV
source can be calculated by applying in (5.10) the measurements of the PV module/array output
voltage, thus avoiding the direct measurement of the corresponding output current. Using the
calculated value of P pv , the P&O algorithm may be applied for executing the MPPT process.
In [44], a flyback inverter operating in the discontinuous conduction mode is connected at the
output of the PV module for interfacing the PV-generated power to the electric grid. The output
power of the PV module (i.e., P pv = V pv ⋅ I pv ) is calculated by measuring the PV module output
voltage and also calculating the PV source output current using the following equation (assuming a
lossless power converter):

1 2 ⋅
I pv = ⋅ D max T s ⋅ V pv (5.11)
4 L m
where
D max is the maximum value of the primary-switch duty cycle during the half period of the electric
grid voltage
T s is the switching period
L m is the magnetizing inductance of the isolation transformer incorporated into the flyback
inverter circuit

A P&O algorithm is also applied in this case for executing the MPPT process using the cal-
culated values of I pv (by 5.11) and P pv . The accuracy of the single-sensor MPPT approaches
is affected by the deviation of the operation of the practical power converter circuit from that
predicted by the theoretical Equations 5.10 and 5.11, respectively, due to the tolerance of the
electric/electronic components values, circuit parasitics, etc. The MPPT accuracy of this method
can be improved if the MPPT control unit is modified such that the deviation mentioned earlier