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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/141327 |
| _version_ | 1811693640075968512 |
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| author | Gupta, Payal Zan, Thaw Tar Thein Dauwels, Justin Ukil, Abhisek |
| 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 |
| author_sort | Gupta, Payal |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T06:54:53Z |
| format | Journal Article |
| id | ntu-10356/141327 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:54:53Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-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. |
| 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 |
| title | 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_short | 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 |
| topic | Engineering::Electrical and electronic engineering Energy Consumption Gas Distribution Network |
| url | https://hdl.handle.net/10356/141327 |
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