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Research Papers: Energy Systems Analysis

Demographical Energy Usage Analysis of Residential Buildings

[+] Author and Article Information
Alice Sokolova

Electrical and Computer Engineering Department,
San Diego State University,
San Diego, CA 92182
e-mail: asokolova@sdsu.edu

Baris Aksanli

Electrical and Computer Engineering Department,
San Diego State University,
San Diego, CA 92182
e-mail: baksanli@sdsu.edu

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received August 27, 2018; final manuscript received December 28, 2018; published online January 18, 2019. Assoc. Editor: Reza Baghaei Lakeh.

J. Energy Resour. Technol 141(6), 062003 (Jan 18, 2019) (6 pages) Paper No: JERT-18-1665; doi: 10.1115/1.4042451 History: Received August 27, 2018; Revised December 28, 2018

Residential energy consumption constitutes a significant portion of the overall energy consumption. There are significant amount of studies that target to reduce this consumption, and these studies mainly create mathematical models to represent and regenerate the energy consumption of individual houses. Most of these models assume that the residential energy consumption can be classified and then predicted based on the household size. As a result, most of the previous studies suggest that the household size can be treated as an independent variable which can be used to predict energy consumption. In this work, we test this hypothesis on a large residential energy consumption dataset that also includes demographic information. Our results show that other variables such as income, geographic location, house type, and personal preferences strongly impact energy consumption and decrease the importance of the household size because the household size can explain only 26.55% of the electricity consumption variation across the houses.

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Figures

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Fig. 1

Southern California Edison average monthly summer month use by income and household size. Images are created using numbers from Ref. [17]: (a) hot climate, (b) mild climate, (c) cool climate, and (d) all.

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Fig. 2

Variation of electricity usage across homes of the same size. Image recreated from Ref. [20].

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Fig. 3

Average house size versus income level. The figure is created using numbers from Residential Energy Consumption Survey [6].

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Fig. 4

Clustering results based on only mean and standard deviation of monthly energy consumption

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Fig. 5

Clustering results based on only household size, and energy consumption is monthly

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Fig. 6

Clustering results based on daily average energy consumption for different family sizes

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Fig. 7

Clustering results with 20-dimensional data, and energy consumption is monthly

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Fig. 8

Clustering results with 40-dimensional data, and energy consumption is hourly

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Fig. 9

The U.S. residential sector electricity consumption by major end uses in 2017. Image created using the table in Ref.[25].

Tables

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