A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems
Joint Authors
Zhu, Changan
Li, Guiqiang
Jin, Yi
Hou, Wenhui
Source
International Journal of Photoenergy
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In order to extract the maximum power from PV system, the maximum power point tracking (MPPT) technology has always been applied in PV system.
At present, various MPPT control methods have been presented.
The perturb and observe (P&O) and conductance increment methods are the most popular and widely used under the constant irradiance.
However, these methods exhibit fluctuations among the maximum power point (MPP).
In addition, the changes of the environmental parameters, such as cloud cover, plant shelter, and the building block, will lead to the radiation change and then have a direct effect on the location of MPP.
In this paper, a feasible MPPT method is proposed to adapt to the variation of the irradiance.
This work applies the glowworm swarm optimization (GSO) algorithm to determine the optimal value of a reference voltage in the PV system.
The performance of the proposed GSO algorithm is evaluated by comparing it with the conventional P&O method in terms of tracking speed and accuracy by utilizing MATLAB/SIMULINK.
The simulation results demonstrate that the tracking capability of the GSO algorithm is superior to that of the traditional P&O algorithm, particularly under low radiance and sudden mutation irradiance conditions.
American Psychological Association (APA)
Hou, Wenhui& Jin, Yi& Zhu, Changan& Li, Guiqiang. 2016. A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems. International Journal of Photoenergy،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1106484
Modern Language Association (MLA)
Hou, Wenhui…[et al.]. A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems. International Journal of Photoenergy No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1106484
American Medical Association (AMA)
Hou, Wenhui& Jin, Yi& Zhu, Changan& Li, Guiqiang. A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems. International Journal of Photoenergy. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1106484
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1106484