University of Tasmania
Browse

File(s) under permanent embargo

A genetic algorithm approach to parameter estimation for PV modules

conference contribution
posted on 2023-05-23, 11:24 authored by Zhang, Y, Sarah LydenSarah Lyden, Bernardo Leon de la Barra, Haque, ME
Accurate modelling of photovoltaic (PV) modules is necessary to understand PV cell operation and to develop maximum power point tracking (MPPT) algorithm for efficient operation of the PV system. A variety of models are proposed in the literature that use a current source, diodes and resistors to represent a PV module. The parameter values involved in the model need to be accurately estimated to improve the model accuracy. The values of the series resistance and diode’s ideality factor could be improved in previous research. This paper proposes a genetic algorithm approach to parameter estimation for PV modules. A parameter estimation technique proposed in previous research is also explored and analyzed. Results show that the proposed parameter estimation technique reduces the errors at the remarkable points when compared to the existing method.

History

Publication title

Proceedings of the 2016 IEEE Power and Energy Society General Meeting

Pagination

1-5

ISBN

978-1-5090-4168-8

Department/School

School of Engineering

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

USA

Event title

2016 IEEE Power and Energy Society General Meeting

Event Venue

Boston, Massachusetts

Date of Event (Start Date)

2016-07-17

Date of Event (End Date)

2016-07-21

Rights statement

Copyright 2016 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Mining and extraction of energy resources not elsewhere classified

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC