Analysis of High Performance MPPT Controllers for Solar Photovoltaic System
DOI:
https://doi.org/10.61841/rqbp2v77Keywords:
Power Conversion Harmonics, DC-DC Power Converters, DC-AC Power Converters, Solar Panels, Maximum Power Point TrackersAbstract
In photovoltaic (PV) power generation, rapidly changing atmospheric conditions are an unavoidable complication that significantly reduces the performance of the system. MPPT is broadly used to extract maximum power under changing atmospheric conditions. Various conventional, soft computing, and meta-heuristic MPPT techniques are compared and implemented to determine their performance under various atmospheric conditions. The MPPT algorithms used in this work are particle swarm optimization (PSO), adaptive neuro fuzzy inference system (ANFIS), artificial neural network (ANN), fuzzy logic control (FLC), incremental conductance (IC), perturb and observe (P&O), and a newly suggested technique for MPPT using the whale optimization algorithm (WOA). The novelty of this work is the whale optimization algorithm (WOA) proposed for MPPT. The parameters considered in determining the performance of MPPT in this work are response time, tracking efficiency, oscillations around maximum power point (MPP), verve condensed to reach stable state, and hardware implementation complexity. The simulation was done in MATLAB/Simulink. The outcome of this analysis is expected to be useful for the investigators functioning in the section of MPPT techniques. This paper likewise fills in as a legitimate reference for future clients in choosing proper MPPT calculations.
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