Forecasting gas demand is critical to pipe reservation and price forecasting.
After presenting statistical characterization of residential, industrial and thermoelectric gas demand, several statistical learning models are applied and compared to perform day-ahead forecasting. Different ensemble models are also considered.

A considerable improvement over the forecasts performed by SNAM, the Italian transmission system operator, is achieved.

Delivered at P-Value Meetup, Pavia, Italy, 29 June 2020
Summary and slides at https://www.meetup.com/it-IT/Data-Science-Meetup-Pavia/events/262410495/