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

This paper 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 p...

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Main Author: Nor Adzman, Nurul Khairaini
Format: Article
Language:English
Published: Universiti Teknologi MARA (UiTM) 2013
Online Access:https://ir.uitm.edu.my/id/eprint/97478/1/97478.PDF
https://ir.uitm.edu.my/id/eprint/97478/
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spelling my.uitm.ir.974782024-06-25T08:57:38Z https://ir.uitm.edu.my/id/eprint/97478/ Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman Nor Adzman, Nurul Khairaini This paper 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. Universiti Teknologi MARA (UiTM) 2013 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/97478/1/97478.PDF Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman. (2013) pp. 1-5.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description This paper 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 Article
author Nor Adzman, Nurul Khairaini
spellingShingle Nor Adzman, Nurul Khairaini
Output prediction of grid-connected photovoltaic system using artificial neural network: article / 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: article / Nurul Khairaini Nor Adzman
title_short Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman
title_full Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman
title_fullStr Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman
title_full_unstemmed Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman
title_sort output prediction of grid-connected photovoltaic system using artificial neural network: article / nurul khairaini nor adzman
publisher Universiti Teknologi MARA (UiTM)
publishDate 2013
url https://ir.uitm.edu.my/id/eprint/97478/1/97478.PDF
https://ir.uitm.edu.my/id/eprint/97478/
_version_ 1802981132742950912
score 13.188404

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