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Hybrid Fuzzy Logic-Based MPPT for Wind Energy Conversion System

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Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1057))

Abstract

Maximum power can be extricated when the turbine keeps running at a consistent and constant speed by using all the vitality present in the wind. The turbine can keep running at a steady speed just when the breeze speed is consistent. The wind vitality being wild in nature, maximum power must be achieved by making the turbine to keep running at the specific breeze speed. To achieve most extreme power, distinctive sorts of maximum power point tracking (MPPT) procedures are utilized. So as to comprehend prudent and proficient power age utilizing wind turbines, modification of fuzzy-based MPPT method is displayed and results are compared with different MPPT techniques for wind energy conversion system have been done and are introduced in subtleties.

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Abbreviations

\(\rho\) :

Air density (1.2 kg/m3)

C p :

Power coefficient

\(\beta\) :

Incident angle of the blade

V in :

Input voltage

V o :

Output voltage

P w :

Wind power

η g :

Generator efficiency

η m :

Motor efficiency

I :

Current

P e :

Electric power generated

E :

Error

DP:

Deviation of power over a small time interval

DV:

Deviation of voltage over a small time interval

DI:

Deviation of current over a small time interval

CE:

Deviation in error

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Author information

Authors and Affiliations

  1. School of Electrical Engineering, VIT University, Vellore, India

    Vankayalapati Govinda Chowdary, V. Udhay Sankar, Derick Mathew, CH Hussaian Basha & C. Rani

Authors
  1. Vankayalapati Govinda Chowdary
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  2. V. Udhay Sankar
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  3. Derick Mathew
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  4. CH Hussaian Basha
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  5. C. Rani
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Corresponding author

Correspondence to Vankayalapati Govinda Chowdary .

Editor information

Editors and Affiliations

  1. Department of Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

  2. Department of Mathematics, South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

  3. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  4. Department of Mathematics, Faculty of Science, Liverpool Hope University, Liverpool, UK

    Atulya K. Nagar

  5. School of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India

    Ponnambalam Pathipooranam

  6. School of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India

    Rani Chinnappa Naidu

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Govinda Chowdary, V., Udhay Sankar, V., Mathew, D., Hussaian Basha, C., Rani, C. (2020). Hybrid Fuzzy Logic-Based MPPT for Wind Energy Conversion System. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1057. Springer, Singapore. https://doi.org/10.1007/978-981-15-0184-5_81

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