Electricity Load Pattern Analysis using Fuzzy C-Means Clustering Algorithm

다국어 초록 (Multilingual Abstract)

Energy consumption has grown explosively in recent years, and energy shortages occurred occasionally. Demand Response (DR) programs could help energy management entities to balance power generation and consumption. The electricity consumption data were collected with the widely deployed advanced smart meters, which contain valuable information. Consumption data can be used to explore the consumption behavior and help Demand Side Management (DSM). This study proposed clustering algoritsshms to obtain the representative load patterns based on diurnal load profiles. First, we applied discrete wavelet transform (DWT) to extract features from 10-second interval daily electricity consumption data. Then using Principal Component Analysis (PCA) for dimensionality reduction. Lastly, implement Fuzzy C-Means (FCM) clustering algorithm to segment preserved features. Additionally, we discuss the clustering result and load pattern analysis of the dataset with respect to the electricity pattern.