This study focuses on analyzing customer load profiles and their impact on the electric distribution grid in the context of the COVID-19 pandemic in the Philippines. With the increasing number of Filipinos working from home, energy consumption has surged, making it crucial for electric distribution companies to classify customer profiles based on energy usage. In this paper, we collected residential data from a Philippine electric distribution company during the COVID-19 pandemic. The objective is to employ clustering methods, particularly the K-means algorithm, to group customer profiles and determine the optimal number of clusters using the multi-criteria model and elbow method. All simulation were performed using MATLAB platform. This study provides valuable insights for electric distribution companies in managing customer load profiles and optimizing the distribution grid amidst the pandemic.
Pandemic Impact on Residential Electricity Customer Load Profile Clustering
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