Summary
International Symposium on Nonlinear Theory and its Applications
2017
Session Number:B2L-C
Session:
Number:B2L-C-1
Evolutionary Computation Based Dynamic Maximum Power Point Tracking
Ryusuke Akeno, Toshimichi Saito,
pp.494-497
Publication Date:2017/12/4
Online ISSN:2188-5079
Summary:
This paper presents the imaginary particle swarm optimizer with reset function (iPSOR) for maximum power point tracking in photovoltaic array under partial shading condition. The cost function corresponds to the voltage-versus-power characteristic of the photovoltaic array. Depending on insolation and temperature, the cost function and its MPP vary in a complicated way. In order to track the dynamic MPP, the iPSOR includes several strategies: imaginary particle swarm consisting of sampled voltages for real-time operation, a flexible reset method of the past history for adaptation to dynamic environment. Performing numerical experiments for basic artificial problems, the efficiency of the iPSOR is confirmed.