Solar power forecasting using sky imagers

Solar energy from the sun is one of the most ancient and reliable energy. It is available widely and easily controlled to minimise our dependence on gasoline or crude oil. Singapore is a nation that is lacking of natural substances and resources therefore it is necessary to build on renewable energy...

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Main Author: Tan, Justine Choon Ping
Other Authors: Gooi Hoay Beng
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/60892
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-608922023-07-07T15:50:37Z Solar power forecasting using sky imagers Tan, Justine Choon Ping Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Solar energy from the sun is one of the most ancient and reliable energy. It is available widely and easily controlled to minimise our dependence on gasoline or crude oil. Singapore is a nation that is lacking of natural substances and resources therefore it is necessary to build on renewable energy and micro-grids to improve and strengthen the efficiency of solar system. This in turn allows us to be better prepared for our own energy needs. The recent trend towards a clean energy market has fastened up the introduction of power generation in Singapore. Many weather parameters and conditions namely irradiance and temperature are deciding factors for the performance of PV systems. A precision estimation tools for solar radiation are critical and important in the design of PV systems. PV has reached grid parity for large scale implementation in Singapore. Lack of predictability of solar power at an acceptable degree of accuracy remains a major hindrance to the introduction of large scale solar energy production. Comprehensive short-term forecasting technologies are required to manage solar energy supply. Therefore it is a necessity to have a better prediction to forecast the solar irradiance needed for the solar power output. Bachelor of Engineering 2014-06-02T08:06:03Z 2014-06-02T08:06:03Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60892 en Nanyang Technological University 63 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Tan, Justine Choon Ping
Solar power forecasting using sky imagers
description Solar energy from the sun is one of the most ancient and reliable energy. It is available widely and easily controlled to minimise our dependence on gasoline or crude oil. Singapore is a nation that is lacking of natural substances and resources therefore it is necessary to build on renewable energy and micro-grids to improve and strengthen the efficiency of solar system. This in turn allows us to be better prepared for our own energy needs. The recent trend towards a clean energy market has fastened up the introduction of power generation in Singapore. Many weather parameters and conditions namely irradiance and temperature are deciding factors for the performance of PV systems. A precision estimation tools for solar radiation are critical and important in the design of PV systems. PV has reached grid parity for large scale implementation in Singapore. Lack of predictability of solar power at an acceptable degree of accuracy remains a major hindrance to the introduction of large scale solar energy production. Comprehensive short-term forecasting technologies are required to manage solar energy supply. Therefore it is a necessity to have a better prediction to forecast the solar irradiance needed for the solar power output.
author2 Gooi Hoay Beng
author_facet Gooi Hoay Beng
Tan, Justine Choon Ping
format Final Year Project
author Tan, Justine Choon Ping
author_sort Tan, Justine Choon Ping
title Solar power forecasting using sky imagers
title_short Solar power forecasting using sky imagers
title_full Solar power forecasting using sky imagers
title_fullStr Solar power forecasting using sky imagers
title_full_unstemmed Solar power forecasting using sky imagers
title_sort solar power forecasting using sky imagers
publishDate 2014
url http://hdl.handle.net/10356/60892
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