Application of improved chicken swarm optimization for MPPT in photovoltaic system

Application of improved chicken swarm optimization for MPPT in photovoltaic system The chicken swarm optimization algorithm is a new biology optimization algorithm, but its high‐dimensional operation usually causes deviation and the iteration time of optimizing is a little long. An improved chicken swarm optimization algorithm is proposed. In the improved algorithm, initial positions are arranged according to chaotic sequence; therefore, the uniformity and ergodicity of population are enhanced. Adaptive inertia weight is introduced to update the rule of hens; thus, the speed of global search and the ability of local search are enhanced. The following coefficient of chicks is changed into random quantity, so the risk of falling into local extremum is avoided. These improvements enhance the search ability in the early stage and the track ability in the late stage of the algorithm. The improved algorithm is applied in the maximum power point tracking control of the photovoltaic system and is compared with other algorithms. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Optimal Control Applications and Methods Wiley

Application of improved chicken swarm optimization for MPPT in photovoltaic system

Loading next page...
 
/lp/wiley/application-of-improved-chicken-swarm-optimization-for-mppt-in-8vRr94nt3P
Publisher
Wiley
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
0143-2087
eISSN
1099-1514
D.O.I.
10.1002/oca.2394
Publisher site
See Article on Publisher Site

Abstract

The chicken swarm optimization algorithm is a new biology optimization algorithm, but its high‐dimensional operation usually causes deviation and the iteration time of optimizing is a little long. An improved chicken swarm optimization algorithm is proposed. In the improved algorithm, initial positions are arranged according to chaotic sequence; therefore, the uniformity and ergodicity of population are enhanced. Adaptive inertia weight is introduced to update the rule of hens; thus, the speed of global search and the ability of local search are enhanced. The following coefficient of chicks is changed into random quantity, so the risk of falling into local extremum is avoided. These improvements enhance the search ability in the early stage and the track ability in the late stage of the algorithm. The improved algorithm is applied in the maximum power point tracking control of the photovoltaic system and is compared with other algorithms.

Journal

Optimal Control Applications and MethodsWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off