Page 118 - IJEEE-2022-Vol18-ISSUE-1
P. 118
114 | Jasim & Jasim
temperature of 25 degrees Celsius. Figure 3 depicts the steady state operation, resulting in fluctuating
adopted PV array characteristics. converter output.
? It can also track in the opposite direction, away
A boost converter is linked to the PV array and MPPT from the MPP, when irradiance levels are quickly
controller controls the boost. The MPP's exact position is increasing or falling.
uncertain, as it shifts with irradiance and temperature. As a
result, the MPPT algorithms serve as guidelines for the Fig.5 can be used to explain the second issue. Assume
MPPT controller to adjust the operating point toward the that the first state was at point A, with a 250 W/m2 irradiance
MPP in any circumstance. The P&O algorithm and fuzzy level. If the irradiance level is suddenly increased to 500
logic approaches have been used in this study. The MPPT W/m2 while the controller is in the process of dropping the
use the Perturb and Observe approach to adjust the voltage voltage, the controller will continue to decrease the voltage,
across the PV array's terminals in order to collect the causing the MPP to mismatch and move toward point B. Any
maximum amount of electricity. The MPPT controller additional increase in irradiance causes the operational point
perturbs the PV voltage by a little amount in this process, and to migrate away from MPP, toward points C and D, rather
the change in output power ?P is then measured. If ?P is than toward points F, R, and H. If the controller was
positive, the operating point moves closer to the MPP, and increasing the voltage action, the tracking would proceed
the controller perturbs in the same direction again to move toward points N, M, and O, causing the same issue. This
closer to that point (Case 1 in Fig. 4). If ?P is negative, the means that during foggy days, the P&O algorithm fails at
operating point is distant from the MPP, and the controller cloudy days.
reverses the direction of the perturbation as a result (Case 2
in Fig. 4). The process is continued until the MPP has been
achieved.
Fig. 3: The adopted PV array characteristics Fig.5 P&O algorithm error tracking under rapidly rising
irradiance.
Working with imprecise inputs, not requiring a perfect
mathematical model, and handling nonlinearity are all
benefits of fuzzy logic controllers [33]. The three steps of
fuzzy logic control are fuzzification, rule basis lookup table,
and defuzzification. In the fuzzification step, membership
functions based linguistic variables similar to that in Fig.6
can be obtained from numerical input variables. NB
(negative large), NS (negative small), ZE (zero), PS (positive
small), and PB (positive big) are the most commonly utilized
membership functions [34]. The crisp values of the
membership functions are represented by "a" and "b" in
Fig.6.
Fig.4. PV Module Power vs. Voltage at (G=1000??/??2, Fig.6: The fuzzy logic control's membership functions.
T=25?).
Although the P&O method is simple to develop, it has
several flaws, including [32]:
? One of the significant disadvantages of the perturb
and observe technique is that the output power
oscillates around the maximum power point under
