Complementary material: Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system

Name: Complementary material: Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system
Creator: Julie Viloria-Porto
Published: 2020-08-14T23:05:31.113Z
Keywords: Computer Science, Artificial Intelligence, Off-Grid Power Supply Systems

Viloria-Porto, Julie; Robles-Algarín, Carlos; Restrepo-Leal, Diego

doi:10.17632/mbt6845jjb.1

Complementary material: Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system

Published: 14 August 2020| Version 1 | DOI: 10.17632/mbt6845jjb.1

Contributors:

Julie Viloria-Porto, Carlos Robles-Algarín, Diego Restrepo-Leal

Description

In this dataset you will find the training algorithms (LMS and RTRL) developed for an ADALINE neural network, used as an MPPT control mechanism in a photovoltaic system completely isolated from the electrical network. Additionally, the results obtained in computational tests (simulation data) and experimental tests carried out in the field are available.

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Universidad del Magdalena

Complementary material: Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system

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