Application of Particle Swarm Optimization to Dynamic Maximum Power Point Tracking

• Tanakajima Kosuke

  The Graduate School of Science and Engineering, Hosei University

• Saito Toshimichi

  The Graduate School of Science and Engineering, Hosei University

Bibliographic Information

Other Title

• 粒子群最適化の動的最大電力点追従への応用

Abstract

This paper considers application of a particle swarm optimization algorithm to the maximum power point tracking in photovoltaic systems. The cost function of a terminal voltage is time-variant in dynamic environment and the voltage corresponds to a particle. Since the terminal voltage can take one value at an instant, it is difficult to construct plural particles. In order to overcome this difficulty, our algorithm uses imaginary particles consisting of sampled values of the terminal voltage. In order to adapt to the dynamic cost function, the algorithm uses a flexible reset method of the personal best. In order to escape from a trap of local solution, the algorithm accelerates particles periodically. Performing basic numerical experiments, the algorithm efficiency is investigated.

Journal

• Transaction of the Japanese Society for Evolutionary Computation

  Transaction of the Japanese Society for Evolutionary Computation 7 (2), 24-31, 2016

  The Japanese Society for Evolutionary Computation

Keywords

• particle swarm optimization
• maximum power point tracking
• photovoltaic systems

Details

• CRID: 1390282680342524032
• NII Article ID: 130005277225
• DOI: 10.11394/tjpnsec.7.24
• ISSN: 21857385
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed