Abstract
A novel maximum power point tracking (MPPT) technique based on mutual coordination of two photovoltaic (PV) modules/arrays has been proposed for distributed PV (DPV) systems. The proposed technique works in two stages. Under non-mismatch conditions between PV modules/arrays, superior performance stage 1 is active, which rectifies the issues inherited by the perturb and observe (P&O) MPPT. In this stage, the technique revolves around the perturb and observe (P&O) algorithm containing an intelligent mechanism of leader and follower between two arrays. In shading conditions, stage 2 is on, and it works like conventional P&O. Graphical analysis of the proposed technique has been presented under different weather conditions. Simulations of different algorithms have been performed in Matlab/Simulink. Simulation results of the proposed technique compliment the graphical analysis and show a superior performance and a fast response as compared to others, thus increasing the efficiency of distributed PV systems.
Highlights
PV systems stand as one of the best renewable sources because of continuous technological advancement, reduced cost and a reliable source
The perturb and observe (P&O) maximum power point tracker (MPPT) has been optimized for various aspects including: (1) the use of variable perturbation size [18]; (2) adaptive perturbation frequency [19]; (3) drift control mechanism [20]; (4) reduced steady state power oscillations [21]; (5) implementation using artificial intelligence and optimization algorithms [22]; (6) hybrid solutions with P&O and other MPPT methods [23,24,25]
For benchmarking the proposed MPPT, two algorithms are compared in simulations which are: (1) dual array based incremental conductance (D-IC) [6,22,23] and (2) conventional P&O running on individual arrays
Summary
PV systems stand as one of the best renewable sources because of continuous technological advancement, reduced cost and a reliable source. The P&O MPPT has been optimized for various aspects including: (1) the use of variable perturbation size [18]; (2) adaptive perturbation frequency [19]; (3) drift control mechanism [20]; (4) reduced steady state power oscillations [21]; (5) implementation using artificial intelligence and optimization algorithms [22]; (6) hybrid solutions with P&O and other MPPT methods [23,24,25] These efforts are based on the use of single/two stage power processing system with centralized PV plant
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