Optimization of maximum demand of electrical energy system using distributed generation technology

Nowadays, the increasing of energy demand and its escalating cost has forced many companies and institutions looking solution for this problem. Electric customers have to pay a maximum demand charge in addition to the usual kWh consumption charge. The peak demand charge frequently stands a large por...

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Main Author:	Hassan, Mohamud Abukar
Format:	Thesis
Language:	English
Published:	2012
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/33738/1/MohamudAbukarHassanMFKK2012.pdf
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spelling	my-utm-ep.337382017-09-20T05:49:40Z Optimization of maximum demand of electrical energy system using distributed generation technology 2012-12 Hassan, Mohamud Abukar TK Electrical engineering. Electronics Nuclear engineering Nowadays, the increasing of energy demand and its escalating cost has forced many companies and institutions looking solution for this problem. Electric customers have to pay a maximum demand charge in addition to the usual kWh consumption charge. The peak demand charge frequently stands a large portion of the total bill and it is based on only a period of 15 or 30 minutes registered during month/billing period. The increase of maximum demand due to the world economic development has created high concern from electric supply companies the need to supply that growth in the short period through the existing facilities. The aim of this research is to optimize maximum demand of electrical energy system using distributed generation technology. The selected case study is Universiti Teknologi Malaysia. In this research on-grid Distributed Generation system (DG) has been used to achieve optimum and minimum peak demand and power cost targets. The on-grid DG was based on Hybrid Power System (HPS) which combines power generated from renewable energy sources such as (PV arrays, wind turbine) and power purchased from grid utility. Micro power optimizer software (HOMER) has been used for the optimization and simulation processes. The results indicate that the maximum demand was reduced 16.5% while a potential cost savings of 14% has been achieved. A sensitivity analysis on resource availability and the system costs has been performed in order to explore how variations in average annual wind speed and solar radiation affect the current optimal system costs. Findings of this study will give a valuable contribution to UTM for analysis pertaining to the development of future optimization of peak demand of electrical energy system. 2012-12 Thesis http://eprints.utm.my/id/eprint/33738/ http://eprints.utm.my/id/eprint/33738/1/MohamudAbukarHassanMFKK2012.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Chemical Engineering Faculty of Chemical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Hassan, Mohamud Abukar Optimization of maximum demand of electrical energy system using distributed generation technology
description	Nowadays, the increasing of energy demand and its escalating cost has forced many companies and institutions looking solution for this problem. Electric customers have to pay a maximum demand charge in addition to the usual kWh consumption charge. The peak demand charge frequently stands a large portion of the total bill and it is based on only a period of 15 or 30 minutes registered during month/billing period. The increase of maximum demand due to the world economic development has created high concern from electric supply companies the need to supply that growth in the short period through the existing facilities. The aim of this research is to optimize maximum demand of electrical energy system using distributed generation technology. The selected case study is Universiti Teknologi Malaysia. In this research on-grid Distributed Generation system (DG) has been used to achieve optimum and minimum peak demand and power cost targets. The on-grid DG was based on Hybrid Power System (HPS) which combines power generated from renewable energy sources such as (PV arrays, wind turbine) and power purchased from grid utility. Micro power optimizer software (HOMER) has been used for the optimization and simulation processes. The results indicate that the maximum demand was reduced 16.5% while a potential cost savings of 14% has been achieved. A sensitivity analysis on resource availability and the system costs has been performed in order to explore how variations in average annual wind speed and solar radiation affect the current optimal system costs. Findings of this study will give a valuable contribution to UTM for analysis pertaining to the development of future optimization of peak demand of electrical energy system.
format	Thesis
qualification_level	Master's degree
author	Hassan, Mohamud Abukar
author_facet	Hassan, Mohamud Abukar
author_sort	Hassan, Mohamud Abukar
title	Optimization of maximum demand of electrical energy system using distributed generation technology
title_short	Optimization of maximum demand of electrical energy system using distributed generation technology
title_full	Optimization of maximum demand of electrical energy system using distributed generation technology
title_fullStr	Optimization of maximum demand of electrical energy system using distributed generation technology
title_full_unstemmed	Optimization of maximum demand of electrical energy system using distributed generation technology
title_sort	optimization of maximum demand of electrical energy system using distributed generation technology
granting_institution	Universiti Teknologi Malaysia, Faculty of Chemical Engineering
granting_department	Faculty of Chemical Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/33738/1/MohamudAbukarHassanMFKK2012.pdf
_version_	1747816173041352704

Optimization of maximum demand of electrical energy system using distributed generation technology

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