Exploring and visualizing household electricity consumption patterns in Singapore: A geospatial analytics approach

Author

Yong Ying TAN, Singapore Management UniversityFollow
Tin Seong KAM, Singapore Management UniversityFollow

Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

4-2019

Abstract

Despite being a small country-state, electricity consumption in Singa-pore is said to be non-homogeneous, as exploratory data analysis showed that the distributions of electricity consumption differ across and within administrative boundaries and dwelling types. Local indicators of spatial association (LISA) were calculated for public housing postal codes using June 2016 data to discover local clusters of households based on electricity consumption patterns. A detailed walkthrough of the analytical process is outlined to describe the R packages and framework used in the R environment. The LISA results are visualized on three levels: country level, regional level and planning subzone level. At all levels we observe that households do cluster together based on their electricity consump-tion. By faceting the visualizations by dwelling type, electricity consumption of planning subzones can be said to fall under one of these three profiles: low-con-sumption subzone, high-consumption subzone and mixed-consumption subzone. These categories describe how consumption differs across different dwelling types in the same postal code (HDB block). LISA visualizations can guide elec-tricity retailers to make informed business decisions, such as the geographical zones to enter, and the variety and pricing of plans to offer to consumers.

Keywords

Electricity Consumption, Exploratory Spatial Data Analysis, Spa-tial Autocorrelation, MITB student

Discipline

Asian Studies | Data Science | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

Information in Contemporary Society: 14th International Conference, iConference 2019, Washington, DC, March 31-April 3: Proceedings

Volume

11420

First Page

785

Last Page

796

ISBN

9783030157418

Identifier

10.1007/978-3-030-15742-5_74

Publisher

Springer

City or Country

Cham

Citation

TAN, Yong Ying and KAM, Tin Seong. Exploring and visualizing household electricity consumption patterns in Singapore: A geospatial analytics approach. (2019). Information in Contemporary Society: 14th International Conference, iConference 2019, Washington, DC, March 31-April 3: Proceedings. 11420, 785-796.
Available at: https://ink.library.smu.edu.sg/sis_research/4376

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.1007/978-3-030-15742-5_74