Single Sensor-Based MPPT of Partially Shaded PV System for Battery Charging by Using Cauchy and Gaussian Sine Cosine Optimization

This paper introduces a battery charging scheme from a solar photovoltaic (SPV) by using a single sensor-based maximum power point tracking (MPPT) strategy. Here, for quick and efficient tracking, a novel hybrid "Cauchy and Gaussian sine cosine optimization" (CGSCO) algorithm is proposed for MPPT, which is based on only a single current sensor. The main objective of the CGSCO algorithm is, maximum extraction of the power from SPV panel and efficiently charging the battery through maximizing the charging current of the battery. Due to the single sensor, the cost of the charging scheme is very low, as well as the algorithm complexity and computational burden are very less, so it can be easily implemented on the low-cost microcontroller. In this paper, a single current sensor-based battery charging scheme by CGSCO algorithm is tested on MATLAB simulator and verified on a developed hardware of the SPV system. The panel condition, with and without shaded as well as dynamic environmental condition (variable temperature and insolation), is considered during simulation as well as on hardware implementation. Moreover, the tracking ability is compared with the most recent state of the art techniques (Grey wolf optimization and Lagrange interpolation particle swarm optimization (LIPSO)) as well as compared with "CGSCO with the conventional dual (voltage and current) sensor-based MPPT scheme." The efficient battery charging with quick MPPT by CGSCO algorithm w.r.t. all state of the art techniques as well as dual sensor-based MPPT scheme, in steady-state as well as in dynamic conditions meets the motive of the work.