Ettore Zanetti

Ettore Zanetti

PhD thesis title: MPC comparisons for residential HVACs and parametric optimization of compact DEC system

Academic Tutor: Livio Mazzarella

Academic Supervisor: Marcello Aprile and Rossano Scoccia

PhD cycle: 34°

BSc: Energy Engineering, Politecnico di Milano

MSc: Energy Engineering, Politecnico di Milano

Lawrance Berkeley National Laboratory, Berkley, United States

Thesis abstract

This thesis aims to study and optimize a compact DEC system named FREESCOO numerically and experimentally. This specific DEC and in general HVAC systems can benefit from advanced control, since it can help reduce discomfort, running cost and environmental impact. Model Predictive Controllers (MPC) have a large variety of possible formulations even for the same HVAC system. This left a gap in literature on the influence of each formulation and solver choice. The aim is to analyze common MPC formulations to find the most suitable methodology and find a way to improve the local controller in a residential scenario using know how coming from an off-line MPC.

Personal interest in my research theme

I was always fascinated with the concept of cheap reliable energy for everyone. Because I consider it the base to increase the quality of life of humanity. At the same time, due to climate change and sustainability goals, energy should also be produced by renewable sources and not wasted. From here my interest in optimal control theory applied to building and energy sector, to allow a further penetration of renewable energy, while also reducing the overall energy consumption.