Application of K-Means Clustering in The Determination of Electrical Profile Characteristics Based on Geographic Information System (GIS)
Adri Senen, Nadiatuljanah, Ginas Alvianingsih · 2024
Mapping the characteristics of a region’s electricity profile is an essential step in energy infrastructure planning and management, especially to understand electricity consumption patterns and power requirements in different areas. Various regions’ electricity systems must be optimized to ensure reliability and efficiency. One way to optimize the electricity system is to conduct an Electricity Profile Characteristic Study. To address this, a study was conducted using the K-Means clustering algorithm to identify and cluster electricity profile characteristics using Geographic Information System (GIS) technology for spatial mapping. Through this method, the electrical profile characteristics of various areas can be analyzed and grouped into clusters. The implementation of GIS allows clustering results to be visualized in thematic maps that facilitate analysis of the spatial distribution of electrical characteristics in each cluster. Based on the results of research conducted in 106 areas involving geographic, demographic, and economic variables and electricity usage patterns at various electricity locations, 7 clusters were obtained. This implementation is expected to be a reference for policy planners in developing electricity infrastructure in the future, especially for developing electricity networks in the regions according to the characteristics of each area.