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International Conference in Artificial Intelligence in Renewable Energetic Systems

ICAIRES 2017: Artificial Intelligence in Renewable Energetic Systems pp 185–196Cite as

MPPT Technique for Standalone Hybrid PV-Wind Using Fuzzy Controller

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 35))

Abstract

This paper present an intelligent technique extraction of Maximum Power Point Tracking (MPPT) by using fuzzy logic from a standalone hybrid generation power system comprising a permanent magnet synchronous generator branch (PMSG) based wind turbine and photovoltaic generator branch compared to the conventional hill climb search (HCS) and Perturb and Observe (P&O) algorithms respectively. The fuzzy controller for solar wind MPPT scheme shows a high precision in current transition and keeps the voltage without any changes, in variable-load case, represented in small steady state error and small overshoot. The proposed scheme ensures optimal use of the photovoltaic (PV) array and PMSG wind proves its efficacy in variable load conditions, unity and lagging power factor at the inverter output (load) side.

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Acknowledgment

This work was financially supported by the ENERGARID and SGRE laboratory and Tahri Mohammed University Béchar 08000 ALGERIA, under the scientific Programme Project Electro-energetique Industrial Option Renewable Energy, 2015/2016.

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Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Technology, Tahri Mohammed University, Route de Kenadsa, BP 417, 08000, Béchar, Algeria

    Saidi Ahmed, Cherif Benoudjafer & Chellali Benachaiba

Authors
  1. Saidi Ahmed
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  2. Cherif Benoudjafer
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  3. Chellali Benachaiba
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Corresponding author

Correspondence to Saidi Ahmed .

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Editors and Affiliations

  1. EPST-CDER, UDES, Unité de Développement des Equipements Solaires, Bou Ismaïl, Algeria

    Mustapha Hatti

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Ahmed, S., Benoudjafer, C., Benachaiba, C. (2018). MPPT Technique for Standalone Hybrid PV-Wind Using Fuzzy Controller. In: Hatti, M. (eds) Artificial Intelligence in Renewable Energetic Systems. ICAIRES 2017. Lecture Notes in Networks and Systems, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-73192-6_19

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  • DOI: https://doi.org/10.1007/978-3-319-73192-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73191-9

  • Online ISBN: 978-3-319-73192-6

  • eBook Packages: EngineeringEngineering (R0)

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