Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman

This project presents an artificial neural network ANN technique for predicting the output from a Grid-Connected Photovoltaic (GCPV) system. In this study, the ANN model utilizes solar irradiance (SI), ambient temperature (AT) and module temperature (MT) as it inputs while the output is the total AC...

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Main Author:	Nor Adzman, Nurul Khairaini
Format:	Thesis
Language:	English
Published:	2013
Online Access:	https://ir.uitm.edu.my/id/eprint/84492/1/84492.pdf
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id	my-uitm-ir.84492
record_format	uketd_dc
spelling	my-uitm-ir.844922024-02-23T03:27:50Z Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman 2013 Nor Adzman, Nurul Khairaini This project presents an artificial neural network ANN technique for predicting the output from a Grid-Connected Photovoltaic (GCPV) system. In this study, the ANN model utilizes solar irradiance (SI), ambient temperature (AT) and module temperature (MT) as it inputs while the output is the total AC power produced from the grid connected PV system. These data was collected from rooftop of Malaysian Green Technology Corporation (MGTC), Bandar Baru Bangi, Malaysia along January and October 2010. The main objective of this research is to predict AC kWh output from grid-connected photovoltaic system referring to its performance indicator. The indicators consist of root mean square error (RMSE) and coefficient of determination (R ), which is for checking the goodness of fit. The performance of ANN model was tested using different algorithm and activation function. The number of neuron has been varied from 1-20 while the momentum rate and the learning rate varies from 0.05 until 1. Levenberg-Marquardt shows the best fit training algorithm. 2013 Thesis https://ir.uitm.edu.my/id/eprint/84492/ https://ir.uitm.edu.my/id/eprint/84492/1/84492.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sulaiman, Shahril Irwan
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Sulaiman, Shahril Irwan
description	This project presents an artificial neural network ANN technique for predicting the output from a Grid-Connected Photovoltaic (GCPV) system. In this study, the ANN model utilizes solar irradiance (SI), ambient temperature (AT) and module temperature (MT) as it inputs while the output is the total AC power produced from the grid connected PV system. These data was collected from rooftop of Malaysian Green Technology Corporation (MGTC), Bandar Baru Bangi, Malaysia along January and October 2010. The main objective of this research is to predict AC kWh output from grid-connected photovoltaic system referring to its performance indicator. The indicators consist of root mean square error (RMSE) and coefficient of determination (R ), which is for checking the goodness of fit. The performance of ANN model was tested using different algorithm and activation function. The number of neuron has been varied from 1-20 while the momentum rate and the learning rate varies from 0.05 until 1. Levenberg-Marquardt shows the best fit training algorithm.
format	Thesis
qualification_level	Bachelor degree
author	Nor Adzman, Nurul Khairaini
spellingShingle	Nor Adzman, Nurul Khairaini Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
author_facet	Nor Adzman, Nurul Khairaini
author_sort	Nor Adzman, Nurul Khairaini
title	Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
title_short	Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
title_full	Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
title_fullStr	Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
title_full_unstemmed	Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman
title_sort	output prediction of grid-connected photovoltaic system using artificial neural network / nurul khairaini nor adzman
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/84492/1/84492.pdf
_version_	1794192008001093632

Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman

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