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Soft computing optimization techniques for solar photovoltaic arrays


Article Information

Title: Soft computing optimization techniques for solar photovoltaic arrays

Authors: Ramaprabha R., Mathur B. L.

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2011

Volume: 6

Issue: 10

Language: English

Categories

Abstract

This paper presents the soft computing optimization techniques to address the Maximum Power Point Tracking (MPPT) of Solar Photovoltaic (SPV) array under partial shaded conditions. Partial shaded SPV modules produce several local maximum power points, which makes the tracking of the Global Maximum Power Point (GMPP) a difficult task. Most of conventional tracking methods fail to work properly under partial shaded conditions. Methods proposed by some authors track the GMPP with some limitations. In this paper, three different soft computing techniques like Genetic algorithm (GA), Differential evolution (DE) and Particle Swarm optimization (PSO) techniques have been applied for GMPP tracking. The performances of these techniques are compared in respect of their tracking time and accuracy.


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