Abstract
In this paper, an interconnected Alternating Current (AC) grid architecture powered by solar photovoltaic energy is conceptualized, evaluated, and implemented to promote rural electrification in developing countries. In order to maximize Photovoltaic (PV) system efficiency, a novel Maximum power point tracking (MPPT) technique is presented in this study that can distinguish between abrupt changes in sunlight and disturbances in the reference voltage. MPPT provides maximum energy conversion efficiency by different solar radiation and temperature environments. Enhanced Incremental Conductance Algorithm (EICA) continuously adjusts the step size to trace the maximum power point more quickly and accurately. Using an enhanced incremental conductance algorithm, this technique adjusts the duty cycle of the DC-DC Boost converter to prevent Maximum Power Point (MPP) divergences that can occur when using a conventional incremental conductance approach under rapidly changing brightness levels. Using simulation in the Matlab / Simulink software, the proposed methodology, which includes a boost converter as the interface to feed the load is tested while accounting for variations in temperature and irradiance. Satisfactory computational findings demonstrate that the Enhanced Incremental Conductance (EIC) method can optimally monitor PV maximum power across a wide range of operational conditions. The EIC-based MPPT tracks the maximum power point more accurately by adjusting the step size according to variations in irradiance. This results in 22% fast convergence and low oscillations at the maximum power point, thereby 15% increasing the efficiency of the photovoltaic system. In addition, the Enhanced Incremental Conductance (EIC) controller, the THD values are relatively lower. The simulation results indicate VTHD of 13.15% and ITHD of 12.31%, whereas the hardware implementation registers VTHD of 14.52% and ITHD of 13.55%.