Solar radiation estimation with neural network approach using meteorological data in Indonesia

The objective of this study is to determine the solar energy potential in Indonesia using artificial neural networks (ANNs) approach. In this study, the meteorological data during 2005 to 2009 from 3 cities (Jakarta, Manado, Bengkulu) are used for training the neural networks and the data from 1 ci...

Full description

Bibliographic Details
Main Authors: Rumbayan, Meita, Nagasaka, Ken
Format: Conference or Workshop Item
Language:English
Published: 2011
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/13614/1/80.pdf
_version_ 1825803217930289152
author Rumbayan, Meita
Nagasaka, Ken
author_facet Rumbayan, Meita
Nagasaka, Ken
author_sort Rumbayan, Meita
collection UUM
description The objective of this study is to determine the solar energy potential in Indonesia using artificial neural networks (ANNs) approach. In this study, the meteorological data during 2005 to 2009 from 3 cities (Jakarta, Manado, Bengkulu) are used for training the neural networks and the data from 1 city (Makasar) is used for testing the estimated values.The testing data are not used in the training of the network in order to give an indication of the performance of the system at unknown locations. Fifteen combinations of ANN models were developed and evaluated.The multi layer perceptron ANNs model, with 7 inputs variables (average temperature, average relative humidity, average sunshine duration, longitude, latitude, latitude, month of the year) are proposed to estimate the global solar irradiation as output.To evaluate the performance of ANN models, statistical error analyses in terms of mean absolute percentage error (MAPE) are conducted for testing data. The best result of MAPE are found to be 7.4% when 7 neurons were set up in the hidden layer.The result demonstrates the capability of ANN approach to generate the solar radiation estimation in Indonesia using meteorological data
first_indexed 2024-07-04T05:53:15Z
format Conference or Workshop Item
id uum-13614
institution Universiti Utara Malaysia
language English
last_indexed 2024-07-04T05:53:15Z
publishDate 2011
record_format eprints
spelling uum-136142015-04-07T04:58:06Z https://repo.uum.edu.my/id/eprint/13614/ Solar radiation estimation with neural network approach using meteorological data in Indonesia Rumbayan, Meita Nagasaka, Ken QA75 Electronic computers. Computer science The objective of this study is to determine the solar energy potential in Indonesia using artificial neural networks (ANNs) approach. In this study, the meteorological data during 2005 to 2009 from 3 cities (Jakarta, Manado, Bengkulu) are used for training the neural networks and the data from 1 city (Makasar) is used for testing the estimated values.The testing data are not used in the training of the network in order to give an indication of the performance of the system at unknown locations. Fifteen combinations of ANN models were developed and evaluated.The multi layer perceptron ANNs model, with 7 inputs variables (average temperature, average relative humidity, average sunshine duration, longitude, latitude, latitude, month of the year) are proposed to estimate the global solar irradiation as output.To evaluate the performance of ANN models, statistical error analyses in terms of mean absolute percentage error (MAPE) are conducted for testing data. The best result of MAPE are found to be 7.4% when 7 neurons were set up in the hidden layer.The result demonstrates the capability of ANN approach to generate the solar radiation estimation in Indonesia using meteorological data 2011-06-08 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/13614/1/80.pdf Rumbayan, Meita and Nagasaka, Ken (2011) Solar radiation estimation with neural network approach using meteorological data in Indonesia. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011, Bandung, Indonesia. http://www.icoci.cms.net.my
spellingShingle QA75 Electronic computers. Computer science
Rumbayan, Meita
Nagasaka, Ken
Solar radiation estimation with neural network approach using meteorological data in Indonesia
title Solar radiation estimation with neural network approach using meteorological data in Indonesia
title_full Solar radiation estimation with neural network approach using meteorological data in Indonesia
title_fullStr Solar radiation estimation with neural network approach using meteorological data in Indonesia
title_full_unstemmed Solar radiation estimation with neural network approach using meteorological data in Indonesia
title_short Solar radiation estimation with neural network approach using meteorological data in Indonesia
title_sort solar radiation estimation with neural network approach using meteorological data in indonesia
topic QA75 Electronic computers. Computer science
url https://repo.uum.edu.my/id/eprint/13614/1/80.pdf
work_keys_str_mv AT rumbayanmeita solarradiationestimationwithneuralnetworkapproachusingmeteorologicaldatainindonesia
AT nagasakaken solarradiationestimationwithneuralnetworkapproachusingmeteorologicaldatainindonesia