Microcontroller based maximum power point tracking through FCC and MLP Neural Networks

Author

Lozito, Gabriele Maria ; Bozzoli, Ludovica ; Salvini, Alessandro

Author_Institution

Dipt. di Ing., Univ. degli Studi di “Roma Tre”, Rome, Italy

fYear

2014

fDate

11-12 Sept. 2014

Firstpage

207

Lastpage

211

Abstract

This paper covers the study towards the implementation of a Neural Network based approach for the efficiency control of Photovoltaic systems. The algorithm aims to track the maximum power point for the PV device whenever abrupt changes in climatic conditions occur. The core of the algorithm is a Neural Network (NN) trained by using a suitable mathematical model of the photovoltaic device. Different NN architectures and several optimization solutions were studied to investigate the best approach in terms of computational efficiency, memory footprint and prediction accuracy. The best found architecture has been implemented and tested on the microcontroller unit LM4F120H5QR by Texas Instruments by using a prototype board to drive the operating point of a low-power solar cell.

Keywords

Texas Instruments computers; maximum power point trackers; microcontrollers; multilayer perceptrons; neurocontrollers; optimisation; photovoltaic power systems; solar cells; FCC; LM4F120H5QR; MLP neural network; NN architecture; PV device; Texas instruments; computational efficiency; efficiency control; fully connected cascade architecture; low-power solar cell; mathematical model; memory footprint; microcontroller based maximum power point tracking; multilayer perceptron; neural network based approach; optimization; photovoltaic device; photovoltaic system; prediction accuracy; prototype board; Artificial neural networks; Computer architecture; FCC; Microcontrollers; Neurons; Temperature measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Education and Research Conference (EDERC), 2014 6th European Embedded Design in

Conference_Location

Milano

Print_ISBN

978-1-4799-6841-1

Type

conf

DOI

10.1109/EDERC.2014.6924389

Filename

6924389