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Optimization of Energy-Aware Flexible Job Shop Scheduling Problem Using VNS-Based GA Approach Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Maximum Power Point Tracking of a Partially Shaded Solar PV Generation System Using Coyote Optimization Algorithm (COA)

Authors : Imran Pervez, Adil Sarwar, Arsalan Pervez, Mohd Tariq, Mohammad Zaid

Published in: Advances in Electromechanical Technologies

Publisher: Springer Singapore

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Abstract

The energy crisis due to population growth and advancements in technology made it mandatory for the researchers to develop some methods that can be helpful in prevention of these crisis. In order to eliminate the day by day growing energy issues, making use of renewable energy sources is considered one of the alternatives. Among these energy sources, solar PV systems are considered one of the most valuable. But the issue with these cells is that they cannot work smartly and cannot detect the optimal power at their output. Hence, in this paper a nature-inspired algorithm Coyote Optimization Algorithm (COA) is used to track maximum power at the output terminal of the solar PV cell.

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previous chapter An Improved Maximum Power Point Tracking (MPPT) of a Partially Shaded Solar PV System Using PSO with Constriction Factor (PSO-CF)
next chapter Design and Simulation of Front-End Converter Based Power Conditioning Unit
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Metadata
Title
Maximum Power Point Tracking of a Partially Shaded Solar PV Generation System Using Coyote Optimization Algorithm (COA)
Authors
Imran Pervez
Adil Sarwar
Arsalan Pervez
Mohd Tariq
Mohammad Zaid
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Electromechanical Technologies

Print ISBN: 978-981-15-5462-9

Electronic ISBN: 978-981-15-5463-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5463-6_44

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