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A new MPPT design using PV-BES system using modified sparrow search algorithm based ANFIS under partially shaded conditions

  • Zuhair Alaas
  • , Galal eldin A. Eltayeb
  • , Mujahed Al-Dhaifallah
  • , Mohsen Latifi*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Nowadays, due to the increasing interest in renewable energy, modeling and practical research on Photovoltaic (PV) have been given much attention. Currently, the challenge of using PV systems is to reach the maximum power point (MPP) in order to increase their efficiency. Hence, extensive research has been done all over the world to develop the productivity of the PV system by properly tracking the MPP. In this regard, in this article, a new maximum power point tracking (MPPT) technique based on Modified Sparrow Search Algorithm and adaptive neuro-fuzzy inference system (ANFIS) is suggested. To implement the suggested MPPT method, two important steps must be taken into account. Firstly, in different conditions of radiation and temperature, the optimal voltage is obtained by mSSA algorithm. Then, the optimal voltage is achieved by the proposed ANFIS method based on different radiation conditions to find the MPP. In order to evaluate the proposed MPPT technique, simulations are done in MATLAB in different weather conditions and scenarios. The results indicate the suitable performance of the recommended mSSA-ANFIS-based MPPT controller in tracking the MPP and achieving the global optimum in different weather conditions by attaining 99.3% efficiency.

Original languageEnglish
Pages (from-to)14109-14128
Number of pages20
JournalNeural Computing and Applications
Volume35
Issue number19
DOIs
StatePublished - Jul 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Control
  • Maximum power point
  • Photovoltaic (PV)
  • Renewable energy

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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