Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia

In order to make accurate energy predictions for large-scale photovoltaic (PV) systems connected to a smart grid, it is first necessary to identify the very specific locations that are required for their long-term optimal operation. Multi-criteria evaluation techniques are often applied for differen...

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Main Authors: Sabo, Mahmoud Lurwan, Mariun, Norman, Hizam, Hashim, Mohd Radzi, Mohd Amran, Zakaria, Azmi
Format: Article
Language:English
Published: Elsevier 2016
Online Access:http://psasir.upm.edu.my/id/eprint/53856/1/Spatial%20energy%20predictions%20from%20large-scale%20photovoltaic%20power%20plants%20.pdf
http://psasir.upm.edu.my/id/eprint/53856/
https://www.sciencedirect.com/science/article/pii/S1364032116303732
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spelling my.upm.eprints.538562018-02-14T07:02:19Z http://psasir.upm.edu.my/id/eprint/53856/ Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia Sabo, Mahmoud Lurwan Mariun, Norman Hizam, Hashim Mohd Radzi, Mohd Amran Zakaria, Azmi In order to make accurate energy predictions for large-scale photovoltaic (PV) systems connected to a smart grid, it is first necessary to identify the very specific locations that are required for their long-term optimal operation. Multi-criteria evaluation techniques are often applied for different site selection studies. This study discusses the past, present and future condition of solar PV application in Malaysia. The study also uses the optimal site definition model (ODM) and GIS to select sites for the installation of large-scale PV power plants that will be connected to a smart grid, and to predict their technical potential and carbon emission reduction, based on optimal sites in Peninsular Malaysia. The outcome of the study reveals that policies and strategies being adopted by Malaysia government are significantly improving the solar PV application for energy sustainability. However, on the other aspect, the results show that 10,092.08 km2 (7.64%) of the area under study is suitable for large-scale PV plant installation. If even half of the potential sites are used, with an installed capacity of 756.91 GW, we predict a total electricity generation potential of 1,343,527.9 GWh/yr with an annual carbon emission reduction of 846,422.56 kt-CO2/yr in Peninsular Malaysia. Based on predicted national energy consumption in 2030, this study shows that about 8 times future annual energy consumption could be met if PV plants with an installed capacity of 756.91 GW are set up in Peninsular Malaysia. Similarly, the study predicts an improvement of 1.6 times the annual carbon emission reduction, based on predicted carbon emissions for 2020. Therefore, the implementation of large-scale PV applications is technically and environmentally viable in Peninsular Malaysia and tropical countries as a whole. Elsevier 2016-12 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/53856/1/Spatial%20energy%20predictions%20from%20large-scale%20photovoltaic%20power%20plants%20.pdf Sabo, Mahmoud Lurwan and Mariun, Norman and Hizam, Hashim and Mohd Radzi, Mohd Amran and Zakaria, Azmi (2016) Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia. Renewable and Sustainable Energy Reviews, 66. pp. 79-94. ISSN 1364-0321; ESSN: 1879-0690 https://www.sciencedirect.com/science/article/pii/S1364032116303732 10.1016/j.rser.2016.07.045
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In order to make accurate energy predictions for large-scale photovoltaic (PV) systems connected to a smart grid, it is first necessary to identify the very specific locations that are required for their long-term optimal operation. Multi-criteria evaluation techniques are often applied for different site selection studies. This study discusses the past, present and future condition of solar PV application in Malaysia. The study also uses the optimal site definition model (ODM) and GIS to select sites for the installation of large-scale PV power plants that will be connected to a smart grid, and to predict their technical potential and carbon emission reduction, based on optimal sites in Peninsular Malaysia. The outcome of the study reveals that policies and strategies being adopted by Malaysia government are significantly improving the solar PV application for energy sustainability. However, on the other aspect, the results show that 10,092.08 km2 (7.64%) of the area under study is suitable for large-scale PV plant installation. If even half of the potential sites are used, with an installed capacity of 756.91 GW, we predict a total electricity generation potential of 1,343,527.9 GWh/yr with an annual carbon emission reduction of 846,422.56 kt-CO2/yr in Peninsular Malaysia. Based on predicted national energy consumption in 2030, this study shows that about 8 times future annual energy consumption could be met if PV plants with an installed capacity of 756.91 GW are set up in Peninsular Malaysia. Similarly, the study predicts an improvement of 1.6 times the annual carbon emission reduction, based on predicted carbon emissions for 2020. Therefore, the implementation of large-scale PV applications is technically and environmentally viable in Peninsular Malaysia and tropical countries as a whole.
format Article
author Sabo, Mahmoud Lurwan
Mariun, Norman
Hizam, Hashim
Mohd Radzi, Mohd Amran
Zakaria, Azmi
spellingShingle Sabo, Mahmoud Lurwan
Mariun, Norman
Hizam, Hashim
Mohd Radzi, Mohd Amran
Zakaria, Azmi
Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
author_facet Sabo, Mahmoud Lurwan
Mariun, Norman
Hizam, Hashim
Mohd Radzi, Mohd Amran
Zakaria, Azmi
author_sort Sabo, Mahmoud Lurwan
title Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
title_short Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
title_full Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
title_fullStr Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
title_full_unstemmed Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia
title_sort spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in peninsular malaysia
publisher Elsevier
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/53856/1/Spatial%20energy%20predictions%20from%20large-scale%20photovoltaic%20power%20plants%20.pdf
http://psasir.upm.edu.my/id/eprint/53856/
https://www.sciencedirect.com/science/article/pii/S1364032116303732
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score 13.18916