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Adaptive fuzzy logic controller as MPPT optimization technique applied to grid-connected PV systems

  • Mohamed M. Refaat
  • , Yousry Atia*
  • , M. M. Sayed
  • , Hossam Abdel Fattah
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

10 Scopus citations

Abstract

This chapter presents a complete design of maximum power point tracking control scheme applied to single-phase single-stage and two-stage grid-connected PV systems based on an adaptive fuzzy controller (AFLC). This technique is proposed to enhance the efficiency of a photovoltaic (PV) array and diminish the output power oscillations. The adaptive nature of the proposed controller provides online tuning of fuzzy rules parameters to deal with varying sun radiation and ambient temperature. Ranges of input variables of fuzzy system are defined using genetic algorithm. The adaptive MPPT controller is compared with existing setups, namely the “incremental conductance” (IC) technique and fuzzy logic controller (FLC). The inverter controller is designed in the synchronous frame so that a simplified controller such as PI-controller is implemented. Simulation and experimental results demonstrate the supremacy of the adaptive technique in terms of the speed of tracking and oscillations reduction around the maximum point of power–voltage (P–V) curve.

Original languageEnglish
Title of host publicationGreen Energy and Technology
PublisherSpringer Verlag
Pages247-281
Number of pages35
DOIs
StatePublished - 2020
Externally publishedYes

Publication series

NameGreen Energy and Technology
ISSN (Print)1865-3529
ISSN (Electronic)1865-3537

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

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

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Industrial and Manufacturing Engineering
  • Management, Monitoring, Policy and Law

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