A novel comprehensive and rigorous analysis of variable step flying squirrel search optimization MPPT controller for renewable energy systems

• Accurate modelling of the PV cell is essential to analyse the solar PV system. • In this work, a triple-diode model PV cell gives accurate PV power. • The proposed FSSVS algorithm provides accurate MPP tracking. • Also, the FSSVS provides high efficiency and less settling time of MPP. The usage of renewable energy systems is increasing day by day when compared to the traditional energy production systems because of the tremendous merits, are huge availability on earth, less air pollution, low-level dependence on the central grids, and easy power production. Here, the solar is considered as the source for supplying the energy to the automobile systems, and the 1 st objective of this work is the development of a triple diode involved PV cell for achieving more accurate nonlinear characteristics of the sunlight system. An MPPT controller is used to catch the operational point of the PV modules. Here, in the 2 nd objective, there are different Maximum Power Point Tracking (MPPT) controllers are investigated to obtain the peak voltage of the PV module at various Partial Shaded Conditions. From the comprehensive investigation, the Flying Squirrel Search Optimization with Variable Step (FSSVS) provides the highest output power of the PV array with the highest efficiency when compared to the Adaptive Cuckoo Search Algorithm (ACSA) and Advanced Particle Swarm Optimization (APSO). Also, this controller utilizes a lower iteration value because of the adjusted step value of the I-V curve of the PV module.