A biomimetic strategy for designing easily-installable CPV tracking system with high wind resistivity

Masaki Yamamoto, Ryutaro Futakuchi, Kazuo Inoue, Hidekazu Arase, Akio Matsushita, Akihiro Itoh, Tetsuya Asano, Nobuhiko Hayashi, Daijiro Inoue, Tohru Nakagawa, Eiji Fujii, Daisuke Ueda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to its higher photovoltaic efficiency, CPV has the advantage of needing a smaller panel footprint than fixed PV systems. This characteristic makes it ideal for use as an independent power supply in remote locations where transportation and site procurement present a challenge. The overall system needs to be compact and light without sacrificing weather resistance. Skilled personnel are scarce in remote areas, so easy setup and maintenance are also important. We have developed two techniques based on the notion of bio-mimicry. One is machine learning to counteract errors in installation position without the need for human intervention, and the other is a three-dimensional panel structure that cuts the wind load by up to 20%. We describe our experimental results gained in field tests.

Original languageEnglish
Title of host publication39th IEEE Photovoltaic Specialists Conference, PVSC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1766-1769
Number of pages4
ISBN (Print)9781479932993
DOIs
StatePublished - 1 Jan 2013
Event39th IEEE Photovoltaic Specialists Conference, PVSC 2013 - Tampa, FL, United States
Duration: 16 Jun 201321 Jun 2013

Publication series

NameConference Record of the IEEE Photovoltaic Specialists Conference
ISSN (Print)0160-8371

Conference

Conference39th IEEE Photovoltaic Specialists Conference, PVSC 2013
CountryUnited States
CityTampa, FL
Period16/06/1321/06/13

Keywords

  • Automatic learning
  • Bio-mimicry
  • Concentrated photovoltaics (CPV)
  • Installation position error
  • Kalman filtering
  • Staggered
  • Tracking
  • Wind force

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