Load forecast for microgrid energy management system (MEMS)

In this 21st century, traditional power generation is no longer sustainable to meet the growing demands of energy consumption from consumers. Over the past decades, increased industrialization and urbanization activities have resulted in depletion of natural resources, global warming, rising inflati...

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Main Author: Choo, Boon Kian.
Other Authors: Gooi Hoay Beng
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/16654
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-166542023-07-07T16:02:19Z Load forecast for microgrid energy management system (MEMS) Choo, Boon Kian. Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution In this 21st century, traditional power generation is no longer sustainable to meet the growing demands of energy consumption from consumers. Over the past decades, increased industrialization and urbanization activities have resulted in depletion of natural resources, global warming, rising inflation and economic instability. A new generation of power generation that focuses on demand side management should be taken into serious consideration. It allows greater freedom, autonomy and responsibility for consumers to plan their own energy consumption. Microgrid, a controllable load from the view point of the main grid, purchases energy from the grid when prices and load demand on the grid are low and likewise, feeds on its own generation when prices and load demand on the grid are high. Microgrid increases the efficiency of cogeneration through district cooling systems. It saves costs and enhances the stability of the system, allowing more communication and participation between the user and the service providers. This thesis aims to provide an overview to the load forecast of a microgrid energy management system based on fuzzy logic and simulation modeling to cater to the presence of fuzziness in load prediction. The same solution algorithm will be used to discuss the forecasted electricity price of MEMS. Bachelor of Engineering 2009-05-28T01:30:11Z 2009-05-28T01:30:11Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/16654 en Nanyang Technological University 72 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::Electric power::Production, transmission and distribution
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution
Choo, Boon Kian.
Load forecast for microgrid energy management system (MEMS)
description In this 21st century, traditional power generation is no longer sustainable to meet the growing demands of energy consumption from consumers. Over the past decades, increased industrialization and urbanization activities have resulted in depletion of natural resources, global warming, rising inflation and economic instability. A new generation of power generation that focuses on demand side management should be taken into serious consideration. It allows greater freedom, autonomy and responsibility for consumers to plan their own energy consumption. Microgrid, a controllable load from the view point of the main grid, purchases energy from the grid when prices and load demand on the grid are low and likewise, feeds on its own generation when prices and load demand on the grid are high. Microgrid increases the efficiency of cogeneration through district cooling systems. It saves costs and enhances the stability of the system, allowing more communication and participation between the user and the service providers. This thesis aims to provide an overview to the load forecast of a microgrid energy management system based on fuzzy logic and simulation modeling to cater to the presence of fuzziness in load prediction. The same solution algorithm will be used to discuss the forecasted electricity price of MEMS.
author2 Gooi Hoay Beng
author_facet Gooi Hoay Beng
Choo, Boon Kian.
format Final Year Project
author Choo, Boon Kian.
author_sort Choo, Boon Kian.
title Load forecast for microgrid energy management system (MEMS)
title_short Load forecast for microgrid energy management system (MEMS)
title_full Load forecast for microgrid energy management system (MEMS)
title_fullStr Load forecast for microgrid energy management system (MEMS)
title_full_unstemmed Load forecast for microgrid energy management system (MEMS)
title_sort load forecast for microgrid energy management system (mems)
publishDate 2009
url http://hdl.handle.net/10356/16654
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