Nature-Inspired Moth Flame Optimization Based MPPT Algorithm for Solar PV System

In recent decades, renewable enrgy especiaaly solar plays a major role in energy generation. Solar photovoltaic (PV) is widely used to generation power from the sun light. Major issue in solar PV power generation is tracking of the peak power from the available multiple power peaks in the operating points. A proper MPPT algorithm is required to capture the maximum power point (MPP) from the characteristic curves of a solar PV under partial shaded conditions (PSC). To select the best optimization model for MPPT under PSC, the nature-inspired moth flame optimization algorithm (MFOA) is used in this work to evaluate the tracking efficiency (TE) of the solar PV systems. From the simulation results, MFOA exhibits a supreme TE of 97.39% which is better than the other algorithms. Similarly the proposed algorithm delivered a 749.48 W of MPPT power and 769.62 W of maximum power <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mathrm{P}_{{\max}})$</tex>.