My research activity is focused on the creation of mathematical models and algorithms that support the way buildings and energy systems are operated. In particular I am interested in how automatic control can help buildings perform better. Model predictive control, state and parameter estimation, are some of the tools I used to investigate how buildings could improve their performances. This article titled If buildings could tell us what's wrong provides a general overview of the research I've done in this area.
Mathematical models are necessary to support the design and operation of buildings and shared energy systems. During the PhD and in the last years I put a lot of effort in modeling a number of different systems, from unconventional HVAC components, control systems, buildings, electrical systems and fluid dynamics. Below you can find a list of papers that describe the work I've done.
Latey I started focusing on data science and statistical methods to understand how energy data can be used to inform people about things that are happening around them. These activities are typically classified as non-intrusive load monitoring (NILM).
Supervisor Prof. Alberto Leva - Politecnico di Milano