Flow-based estimation and comparative study of gas demand profile for residential units in Singapore

The 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, th...

Full description

Saved in:
Bibliographic Details
Main Authors: Gupta, Payal, Zan, Thaw Tar Thein, Dauwels, Justin, Ukil, Abhisek
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141327
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-141327
record_format dspace
spelling sg-ntu-dr.10356-1413272021-01-08T07:30:42Z Flow-based estimation and comparative study of gas demand profile for residential units in Singapore Gupta, Payal Zan, Thaw Tar Thein Dauwels, Justin Ukil, Abhisek School of Electrical and Electronic Engineering Energy Research Institute @ NTU (ERI@N) Engineering::Electrical and electronic engineering Energy Consumption Gas Distribution Network The 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. NRF (Natl Research Foundation, S’pore) 2020-06-08T00:57:58Z 2020-06-08T00:57:58Z 2018 Journal Article Gupta, 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.2018.2861821 1949-3029 https://hdl.handle.net/10356/141327 10.1109/TSTE.2018.2861821 2-s2.0-85050989172 3 10 1120 1128 en IEEE Transactions on Sustainable Energy © 2018 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Energy Consumption
Gas Distribution Network
spellingShingle Engineering::Electrical and electronic engineering
Energy Consumption
Gas Distribution Network
Gupta, Payal
Zan, Thaw Tar Thein
Dauwels, Justin
Ukil, Abhisek
Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
description The 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Gupta, Payal
Zan, Thaw Tar Thein
Dauwels, Justin
Ukil, Abhisek
format Article
author Gupta, Payal
Zan, Thaw Tar Thein
Dauwels, Justin
Ukil, Abhisek
author_sort Gupta, Payal
title Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
title_short Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
title_full Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
title_fullStr Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
title_full_unstemmed Flow-based estimation and comparative study of gas demand profile for residential units in Singapore
title_sort flow-based estimation and comparative study of gas demand profile for residential units in singapore
publishDate 2020
url https://hdl.handle.net/10356/141327
_version_ 1688665533977722880