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2017 | 132 | 3 | 1134-1139
Article title

An Advanced Particle Swarm Optimization Algorithm for MPPTs in PV Systems

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Content
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Languages of publication
EN
Abstracts
EN
Maximum power point trackers are in charge of absorbing the maximum potential power from the photovoltaic panels. Thus, this makes the maximum power point trackers the fundamental parts of the photovoltaic panel systems. The conventional maximum power point tracker algorithms are working well under balanced insolation conditions, however when the partial shade condition occurs, those algorithms are trapped at the local maxima. Hence, under partial shade conditions, the need for a global maximum power point tracking algorithm arises. Particle swarm optimization is a preferential algorithm of maximum power point trackers in literature, especially in partial shade conditions. This paper is focused on improving the existing particle swarm optimization algorithm for maximum power point trackers. The proposed advanced particle swarm optimization algorithm aims to catch the global maximum power point much faster, accurately and to reduce the chatter in the power curve. The proposed method accelerates the global maximum tracking time with gridding the initial search area. The effectiveness of the proposed method is demonstrated with simulation results and these results are compared with a conventional particle swarm optimization method under step changes in irradiance and partial shade conditions of an array of photovoltaic panels.
Keywords
EN
Publisher

Year
Volume
132
Issue
3
Pages
1134-1139
Physical description
Dates
published
2017-09
Contributors
author
  • Sakarya University, Department of Electrical and Electronics Engineering, Sakarya, Turkey
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-app132z3-iip084kz
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