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Flow-Based Estimation and Comparative Study of Gas Demand Profile for Residential Units in Singapore

机译:基于流量的新加坡居民住宅燃气需求曲线估算和比较研究

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摘要

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.
机译:住宅部门构成了大量的能源消耗者;因此,这是减少能耗的重点。为此,对电力和天然气的客户负荷分布图的充分了解对于提高能源利用效率至关重要。不幸的是,由于成本限制,基于小时的能源负荷概况无法直接与能源供应商联系。在本文中,我们提出了一个数学模型,用于使用新加坡居民部门的天然气网络流量数据建立天然气负荷曲线。此外,我们对家庭燃气和电力负荷曲线进行了比较研究。气体流量数据是通过直接连接到新加坡的气体分配网络的真实实验装置生成的,而电负载数据是通过安装在新加坡南洋理工大学住房单元中的智能电表生成的。通过实验显示并通过EMA统计数据进行了验证,每天的天然气消耗量大约比每天的电力消耗低四倍。此外,还介绍了工作日和周末在用电量和用气量方面的区别。这项工作可以作为基准研究,以设计新加坡天然气和电力消耗的低成本预测模型,以有效规划天然气和电力网络。

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