Abstract

Solar energy is the base for both photovoltaic (PV) power generation and plant growth. Inspired by this biological phenomenon, a novel crowded plant height optimisation (CPHO) algorithm was developed for solar PV maximum power point tracking (MPPT). This CPHO-tuned MPPT algorithm was developed with the aim of obtaining the optimal duty cycle (d) for DC-DC boost converter for maximum solar power extraction from PV panels with the help of a proportional-integral controller. Crowded plants regulate the growth of their stem height in relation to neighbouring plants, also known as height convergence. Using this CPHO-algorithm, the stable height of the plant found in a numerical value is taken as the optimal height of the plant. This optimal numerical value was converted into (d) for the converter. Under dynamic weather conditions, the (d) was optimally adjusted by the proposed algorithm to regulate the DC output of the converter. On the utility side, d–q vector control-based voltage source inverter was used for PV power integration into the grid. The performance of the converter control strategy of the proposed CPHO algorithm was compared with perturb and observe algorithm-based MPPT control, which was analysed on MATLAB/Simulink platform.

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