ABSTRACT
This paper presents a proposal methodology to study the temperature dependence of the Italian electricity demand. Indeed, weather temperature has a significant influence on the electricity consumption. From a Transmission System Operator (TSO) perspective, an accurate estimation of this effect is crucial to interpret and predict demand fluctuations. Several dispatching applications consider these phenomena, as for example adequacy analysis, demand forecasting tools, and real-time operational procedures. Based on the geographical features of Italy, it was possible to identify various sensitivity behaviors at regional scale. The purpose of this study is to develop a temperature sensitivity model to be applied on electricity demand profile with different time granularity (e.g., daily, hourly). A clustering analysis on the historical input data is performed. Furthermore, a thorough investigation to identify the optimal best-fitting method for this application is described. In order to test the methodology, some relevant business cases are simulated considering also extreme scenarios. Results on COVID-19 scenario is also described. Finally, an outlook on the planned future developments of the method is provided. © 2021 AEIT.