Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/141327
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dc.contributor.authorGupta, Payalen_US
dc.contributor.authorZan, Thaw Tar Theinen_US
dc.contributor.authorDauwels, Justinen_US
dc.contributor.authorUkil, Abhiseken_US
dc.date.accessioned2020-06-08T00:57:58Z-
dc.date.available2020-06-08T00:57:58Z-
dc.date.issued2018-
dc.identifier.citationGupta, P., Zan, T. T. T., Dauwels, J., & Ukil, A. (2019). Flow-based estimation and comparative study of gas demand profile for residential units in Singapore. IEEE Transactions on Sustainable Energy, 10(3), 1120-1128. doi:10.1109/TSTE.2018.2861821en_US
dc.identifier.issn1949-3029en_US
dc.identifier.urihttps://hdl.handle.net/10356/141327-
dc.description.abstractThe residential sector forms a substantial energy consumer; therefore, it is the focus of efforts to reduce energy consumption. To this end, a good understanding of customer load profiling for both the electricity and gas is fundamental to improve the energy utilization efficiency. Unfortunately, the hourly based energy load profiles are not directly available with the energy suppliers due to cost constraints. In this paper, we propose a mathematical model to build gas load profiles using the gas network flow data for the residential sector in Singapore. In addition, we conduct a comparative study between the household gas and electricity load profiles. The gas flow data is generated from a real experimental setup, directly connected to the gas distribution network of Singapore, while the electricity load data is generated from the smart meters installed at the housing units at Nanyang Technological University, Singapore. It is experimentally shown and also validated from EMA statistics that the daily gas consumption is approximately four times lower than the daily electricity consumption. Moreover, the differentiation between the weekdays and weekend for both the electricity and gas usage profiles is also presented. This work can serve as a benchmark study for designing the low-cost prediction models for gas and electricity consumption in Singapore for effective planning of both the gas and electricity networks.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Sustainable Energyen_US
dc.rights© 2018 IEEE. All rights reserved.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleFlow-based estimation and comparative study of gas demand profile for residential units in Singaporeen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.researchEnergy Research Institute @ NTU (ERI@N)en_US
dc.identifier.doi10.1109/TSTE.2018.2861821-
dc.identifier.scopus2-s2.0-85050989172-
dc.identifier.issue3en_US
dc.identifier.volume10en_US
dc.identifier.spage1120en_US
dc.identifier.epage1128en_US
dc.subject.keywordsEnergy Consumptionen_US
dc.subject.keywordsGas Distribution Networken_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
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