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: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/33738/1/MohamudAbukarHassanMFKK2012.pdf |
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| Summary: | 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. |
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