Maximum power point tracking for Photovoltaic systems using fuzzy logic and artificial neural networks

A. M.Zein Alabedin, E. F. El-Saadany, M. M.A. Salama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

70 Scopus citations

Abstract

The maximum power point tracking (MPPT) aims to increase the efficiency of Photovoltaic (PV) systems by operating their PV panels at the optimum power point. Many strategies have been introduced to achieve this objective. However, these strategies vary in their tracking performance, computational complexity and cost. The rapid changes in environmental conditions and the nonlinearity in the current-voltage (I-V) characteristics of PV panels make the tracking problem complex. This paper presents the design of two controllers; one based on fuzzy logic, and the other based on artificial neural networks. Fuzzy logic controllers are simple, easy to implement, and does not need knowledge of the mathematical model of the system. Neural networks are known to be universal approximators for non-linear dynamic system. Thus, they can be used to estimate the reference parameters of the maximum power point. The two controllers are simulated under variable environmental factors to study their tracking performance.

Original languageBritish English
Title of host publication2011 IEEE PES General Meeting
Subtitle of host publicationThe Electrification of Transportation and the Grid of the Future
DOIs
StatePublished - 2011
Event2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future - Detroit, MI, United States
Duration: 24 Jul 201128 Jul 2011

Publication series

NameIEEE Power and Energy Society General Meeting
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future
Country/TerritoryUnited States
CityDetroit, MI
Period24/07/1128/07/11

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