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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM37643

Artificial Intelligence Based BLDC Motor-Driven Solar PV Fed Water Pumping System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM37643

Volume:

8 |

9 |

Sep 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM37643

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GSP

Gudala Satya Pratap

DM

Dr Midhunchakkaravarthy

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Abstract

The best alternative to the conventional sources of energy is ever lasting solar energy and it is one among the cheapest and widely used energy. The present paper deals with the design and analysis of zeta converters, as it has been used as intermediate between voltage source inverter (VSI) and solar PV array. Maximum power point tracking (MPPT) technique has been used for gaining maximum efficiency from solar PV array. In this paper, Artificial Intelligence(AI) Technique based Fuzzy logic controller is used for better results. When compared to other methods of MPPT technique, Fuzzy logic based MPPT technique is best because it provides better results for randomly varying atmospheric conditions. In our proposed system, BLDC motor which has higher efficiency and noise less operation is considered. Maximum power loss of PV generator is well matched with the load characteristic of BLDC motor. Matlab/Simulink results carried out for the different topology of the DC-DC converters and the results are analyzed and compared.

KEYWORDS

Photovoltaic(PV) system Maximum power point tracking (MPPT) Artificial Intelligence (AI) Technique Fuzzy logic controller BLDC motor zeta converters.

Cite This Article

Gudala Satya Pratap, Dr Midhunchakkaravarthy, "Artificial Intelligence Based BLDC Motor-Driven Solar PV Fed Water Pumping System," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 9, Sep 2024. https://doi.org/10.55041/IJSREM37643

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Publication Date

9/27/2024

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Double-Blind Peer Review

Review Rounds: 2

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5

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