Presentation 2016-09-15
A PSO with Pbest reset and its application to dynamic maximum power point tracking
Kosuke Tanakajima, Ryusuke Akeno, Toshimichi Saito,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper presents a particle swarm optimizer algorithm for the maximum power point tracking in time-variant photovoltaic systems. In order to avoid trapping into local optima, the algorithm accelerates periodically velocity of particles. In order to follow the time-variant characteristics, the optimizer uses a flexible renewal method of the personal best. The algorithm uses only one particle and sampled values of the particle position at several time steps are used as plural particles in real environment. Performing basic numerical experiments, the algorithm efficiency is investigated.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) particle swarm optimization / maximum power point tracking
Paper # NLP2016-61
Date of Issue 2016-09-07 (NLP)

Conference Information
Committee NLP
Conference Date 2016/9/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Konan Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Hisato Fujisaka(Hiroshima City Univ.)
Vice Chair Masaharu Adachi(Tokyo Denki Univ.)
Secretary Masaharu Adachi(Konan Univ.)
Assistant Hiroyuki Asahara(Okayama Univ. of Science) / Toshihiro Tachibana(Shonan Inst. of Tech.)

Paper Information
Registration To Technical Committee on Nonlinear Problems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A PSO with Pbest reset and its application to dynamic maximum power point tracking
Sub Title (in English)
Keyword(1) particle swarm optimization
Keyword(2) maximum power point tracking
1st Author's Name Kosuke Tanakajima
1st Author's Affiliation Hosei University(Hosei Univ.)
2nd Author's Name Ryusuke Akeno
2nd Author's Affiliation Hosei University(Hosei Univ.)
3rd Author's Name Toshimichi Saito
3rd Author's Affiliation Hosei University(Hosei Univ.)
Date 2016-09-15
Paper # NLP2016-61
Volume (vol) vol.116
Number (no) NLP-215
Page pp.pp.89-92(NLP),
#Pages 4
Date of Issue 2016-09-07 (NLP)