ETD

• analysis
• classification
• clustering
• forecasting

In this work we use clustering algorithms to compute the typical Italian load profile
in different days of the week in different seasons. This result can be exploited by energy
providers to tailor more attractive time-varying tariffs for their customers. In addition, we
propose a day ahead load trend forecasting method based on clustering output.