Load profiling of Singapore buildings for peak shaving

This paper carries out load profiling of Singapore housing units and office buildings using bottom-up method for peak load reduction through optimization. Housing units in Singapore are classified according to the number of rooms, ranging from one to five. Average daily, monthly and yearly elec...

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Main Authors: Chuan, Luo, Rao, D. M. K. K. Venkateswara, Ukil, Abishek
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2015
Subjects:
Online Access:https://hdl.handle.net/10356/107081
http://hdl.handle.net/10220/25494
http://dx.doi.org/10.1109/APPEEC.2014.7065998
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1070812019-12-06T22:24:18Z Load profiling of Singapore buildings for peak shaving Chuan, Luo Rao, D. M. K. K. Venkateswara Ukil, Abishek School of Electrical and Electronic Engineering IEEE PES Asia-Pacific Power & Energy Engg. Conference–APPEEC(6th:2014:Hong Kong) DRNTU::Engineering::Electrical and electronic engineering::Power electronics This paper carries out load profiling of Singapore housing units and office buildings using bottom-up method for peak load reduction through optimization. Housing units in Singapore are classified according to the number of rooms, ranging from one to five. Average daily, monthly and yearly electrical usage of all these units is obtained. To explore the strategies for peak load reduction, a mathematical model based on bottom-up method is created. Statistical data - hourly probability factors, frequency of daily operations, saturation levels and nominal wattage of appliances - are gathered for typical Singapore households, and load profiles are generated. The accuracy of the bottom-up model is verified by comparing the load data of a typical three-rooms housing unit in Nanyang Technological University. Then, the problem of peak load reduction is formulated into an optimization problem with peak load as cost function and hourly probability factors of certain appliances as decision vaiables. Solution to the optimal hourly probability factors is obtained using genetic algorithm and it is demonstrated through numerical simulations that about 40% reduction in peak load can be achieved. Finally, some statistical information on load estimation for office buildings is presented. Accepted version 2015-05-11T04:44:54Z 2019-12-06T22:24:18Z 2015-05-11T04:44:54Z 2019-12-06T22:24:18Z 2014 2014 Conference Paper Chuan, L., Rao, D. M. K. K. V., & Ukil, A. (2014). Load profiling of Singapore buildings for peak shaving. IEEE PES Asia-Pacific Power & Energy Engg. Conference–APPEEC(6th:2014:Hong Kong), 1-6. https://hdl.handle.net/10356/107081 http://hdl.handle.net/10220/25494 http://dx.doi.org/10.1109/APPEEC.2014.7065998 en © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [Article DOI: http://dx.doi.org/10.1109/APPEEC.2014.7065998]. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Power electronics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Power electronics
Chuan, Luo
Rao, D. M. K. K. Venkateswara
Ukil, Abishek
Load profiling of Singapore buildings for peak shaving
description This paper carries out load profiling of Singapore housing units and office buildings using bottom-up method for peak load reduction through optimization. Housing units in Singapore are classified according to the number of rooms, ranging from one to five. Average daily, monthly and yearly electrical usage of all these units is obtained. To explore the strategies for peak load reduction, a mathematical model based on bottom-up method is created. Statistical data - hourly probability factors, frequency of daily operations, saturation levels and nominal wattage of appliances - are gathered for typical Singapore households, and load profiles are generated. The accuracy of the bottom-up model is verified by comparing the load data of a typical three-rooms housing unit in Nanyang Technological University. Then, the problem of peak load reduction is formulated into an optimization problem with peak load as cost function and hourly probability factors of certain appliances as decision vaiables. Solution to the optimal hourly probability factors is obtained using genetic algorithm and it is demonstrated through numerical simulations that about 40% reduction in peak load can be achieved. Finally, some statistical information on load estimation for office buildings is presented.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Chuan, Luo
Rao, D. M. K. K. Venkateswara
Ukil, Abishek
format Conference or Workshop Item
author Chuan, Luo
Rao, D. M. K. K. Venkateswara
Ukil, Abishek
author_sort Chuan, Luo
title Load profiling of Singapore buildings for peak shaving
title_short Load profiling of Singapore buildings for peak shaving
title_full Load profiling of Singapore buildings for peak shaving
title_fullStr Load profiling of Singapore buildings for peak shaving
title_full_unstemmed Load profiling of Singapore buildings for peak shaving
title_sort load profiling of singapore buildings for peak shaving
publishDate 2015
url https://hdl.handle.net/10356/107081
http://hdl.handle.net/10220/25494
http://dx.doi.org/10.1109/APPEEC.2014.7065998
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