Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/60892
Title: Solar power forecasting using sky imagers
Authors: Tan, Justine Choon Ping
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2014
Abstract: 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.
URI: http://hdl.handle.net/10356/60892
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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