Investigation of Binary Search Algorithm as Maximum Power Point Tracking Technique in Solar PV System
This paper describes a study in maximum power point tracking (MPPT) technique for photovoltaic (PV) system using binary search algorithm (BSA). The aim of this study is to identify the effectiveness of BSA in performing MPPT under constant irradiance and rapid change irradiance conditions. The BSA MPPT model, together with a well-established particle swarm optimization (PSO) algorithm were developed and implemented with a DC-DC boost converter in MATLAB Simulink. Direct control strategy was implemented to simplify the development of the controller which generates the switching duty cycle of the power converter. In order to examine the performance of both algorithms, five different constant irradiance test cases and four rapid changing irradiance test cases were imposed to the PV system to examine the capability of the both algorithms. BSA exhibits a faster convergence speed with zero steady state oscillation. Both of the algorithms have shown the capability to adapt the rapid change irradiance condition effectively with tracking efficiency up to 99%.
KeywordsMaximum power point tracking Particle swarm optimization Binary search algorithm
The authors would like to thank Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang for supporting this work under research grant RDU160151 and PGRS170351.
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