Performance Comparison of Maximum Power Point Tracking Method of Human Psychology Optimization (HPO), Artificial Bee Colony (ABC) and Fuzzy Logic Controller (FLC) on Flyback Converter Under Partial Shading Condition
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Keywords
MPPT, Human Psychology Optimization, Artificial Bee Colony, Fuzzy Logic Controller, Partial Shading
Abstract
Maximum Power Point Tracking (MPPT) is a method to track the power point of an energy source with the intention to generate maximum power. The surface of the Solar Panel has the possibility of being blocked when it receives sunlight. The barrier can be in the shape of shadows of objects that are nearby solar panels. The problem causes the power generated to be not optimal and makes more than one MPPT peak on the characteristics of P-V. This paper compares several methods of MPPT such as Human Psychology Optimization (HPO), Artificial Bee Colony (ABC), and Fuzzy logic Controller (FLC) under partial shading conditions, the comparison of three method by simulation. This algorithm hooks up to a flyback converter to provide MPP. From the results of MPPT accuracy in partial shading situations, the ABC and HPO approach methods can achieve GMPP with more than 82.22 % accuracy. For convergence, ABC needs extra time to discover GMPP. From the results, the Fuzzy approach can track however nevertheless trapped on LMPP.
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