Abstract:
Renewable energy resources play a vital role in producing electrical energy. In these
renewable resources, the sun is the most important source of energy for production of
electricity. Solar energy is converted into electrical energy using solar cells. Electricity
and voltages generated by solar cells are lower than its ideal values because of variations
in irradiance and temperature during day-time. DC-DC boost converter is designed to
boost the voltages in a desired range. This work compares several control approaches used
to maximize power point tracking. MPPT algorithm Perturb and Observe (P&O) is applied
with Proportional-Integral control to get MPP efficiently. The model for DC-DC boost
converter with controller is implemented in MATLAB/Simulink. A fuzzy logic control
based MPPT algorithm is also implemented for this model and fuzzy rules are made to get
maximum power point. A sliding mode control is also applied in this model. A
comparative analysis of the results of these three controllers is done in this study by
comparing the simulation results achieved in MATLAB/Simulink. The Proposed sliding
mode control have less voltage fluctuation than FLC and P&O/PI. Fuzzy logic controller
has less settling time and higher power tracking speed as compared to SMC and P&O/PI.
A data-based simulation was also run by collecting data of irradiance and temperature
from USPCASE, NUST for a specific day. Results show the output power for the whole
day changes as per change in irradiance and temperature.
