Customers Characterization by Seasonality Detection in Residential Electricity Consumptions Data, Based on High-Day Frequency Identification

The Electrical Distribution Network (EDN) is a critical infrastructure, thus understanding its customers load patterns is essential for the optimal network operation. This paper underscores the importance of identifying customers by seasonal load variations. Seasonal fluctuations affect network operation, and improves resource planning. To address this, we present an innovative algorithm for detecting and identifying electricity customers with weekly seasonal load patterns, and specify the days of the week exhibiting seasonal load behavior. Leveraging advanced analytics, our algorithm enables utilities to tailor services, implement targeted strategies, and enhance smart grid efficiency.