Design and Simulation of GA and Incremental Conductance MPPT Controllers for Enhanced Solar PV Power Extraction

Abstract

Reducing reliance on non-renewable energy sources is essential to address global warming. Solar energy is a promising and abundant option in India. Photovoltaic (PV) cells capture sunlight and convert it into electrical energy; typical PV cells can convert about 20% of incoming solar energy into electricity. A PV cell’s output depends on solar irradiation, cell temperature, and terminal voltage, and the maximum power point (MPP) varies with these conditions. Therefore, effective maximum power point tracking (MPPT) is necessary to operate the PV system at its optimal point.

This work presents a comparative study of two MPPT methods implemented in MATLAB/Simulink: the incremental conductance (INC) method and a genetic algorithm (GA)-based method. The simulations consider varying irradiation and temperature conditions. The GA-based MPPT produced a boosted output voltage of 502.13 V, while the INC method produced 501.50 V. For variable irradiation, the boost converter output power was 92.26 kW for GA and 90.41 kW for INC. These results indicate that the GA-based method outperforms the INC method in terms of overall performance.