We are studying machine-learning algorithms that allow us to forecast wind farm production and estimate in advance our customers’ demand for gas. To do it, we cross-reference historical data, meteorological information and real time data from our installations.

The generation of compressed air is the basis for many industrial processes, that’s why we have studied a mathematical model that, by analysing the historical operational data and cross-referencing them with environmental data, can find the perfect combination of power of the compressors at any time.

The introduction of intelligent meters has made available a large mass of data regarding how and when families consume electricity. Starting with these data, we have created algorithms able to identify different types of consumption so that we can present our customers with ad hoc offers based on their actual use of electricity.

Officine Edison Milano is also at work to guarantee current and possible future customers the simplest and most enjoyable interaction at any stage, from signing a supply contract to relations with the assistance services. To do this, we analyse all points of interaction, identifying the critical points on which to take action.

A company is often characterised by a large number of repetitive actions of low added value; artificial intelligence and bots can take over these activities, leaving us more time for thinking with high cognitive content. Unlike other projects, this does not have a defined time span but is continuous and across-the-board of all the corporate processes. 

There are two research laboratories within Officine, the first entirely dedicated to storage systems for domestic use coupled with photovoltaic systems; the second is used for testing IoT and smarthome tools. The aim of these laboratories is to analyse the actual performance of IoT devices, batteries and technologies and identify the best models to offer our customers.