HVAC systems in buildings are evolving and becoming increasingly complex systems that comprehend various mechanical and electrical components. Thus, the main challenge is to generate and distribute heat or cooling in the most efficient way to lower consumptions and ensure indoor comfort. This can be achieved by substituting low-efficiency generators (boilers, chillers, air treatment units…), increasing the envelope insulation or installing low transmittance windows and doors etc. However, it is worth mentioning that there is a hidden and extensive potential of energy consumption reduction given by Artificial Intelligence algorithms based on optimization control strategies applied to HVAC system. The control system proposed in this paper embodies two different levels: the first and lower one (lvl. 1) manages chillers, pumps and cooling towers while the second is a supervisory control level (lvl. 2) that optimizes thermal production by implementing optimization-based control algorithms that minimize energy consumption and ensure customer needs.
Our work shows many applications of such lvl. 1 logics such as water exchanger approach for temperature control, chiller heat balance, optimal chiller sequencing and optimal chiller loading. Similarly, applications on level 2 include modulation of the supply temperature subject also to indoor temperature comfort boundaries, load balancing in Air Handling Units (AHU) heating coils, predictive control algorithms that use other available information from the BMS (Building Management System) such as forecasted occupancy.
The two-layers control system proposed has been deployed in a Northern Italy airport where it operates the AHUs of different terminals by including external temperatures and flight timetable in the view of reducing energy consumption and ensuring air comfort for passengers. Results have demonstrated an increase of internal comfort for terminal passengers regarding temperature and air ventilation given by a better HVAC management and, at the same time, a lower energy consumption up to 58%.


My name is Filippo Bernardello, I’ve been involved in HVAC control and optimization since 2013 in Mitsubishi Electric Hydronics & IT Cooling Systems, after that I was in charge of the European branch of Conserve It and now, I am the BU manager at Alperia Green Future, one of the biggest Italian ESCo.
Education and qualifications
• University of Padua [IT]
o Master in Computer Engineering (Oct.2008- Apr.2011).Score achieved:105/110. Dissertation title:“On new public-key cryptosystems based on group theory”.
o Bachelor in Computer Engineering (Oct.2005- Oct.2008).Score achieved:95/110. Dissertation title:”On quantum algorithms in computer engineering”.
o Professional computer engineering license achieved in feb.2012(Italian professional practice examination).
o University of Aberdeen [UK]Residence time: (Feb.2009- June2009).Subjects studied: Human-Computer Interaction, Distribuited Information System, Enterprise Computing, Computer-Hardware and Robotics.
• High school“F.Severi”, Padua [IT]High school leaving qualifications in Computer Science (Sep.2000- June2005).Score achieved:78/100
Work experience
• Business Unit Manager at Alperia Green Future in Soave [IT] (November 2021 →).
• EMEA product manager at Conserve It S.R.L. in Padova [IT] (March 2019 → October 2021).
• Visiting engineer at Airmaster Australia PTY LTD e Conserve It PTY LTD in Melbuorne, Australia (2013 – 2016).
• Project manager at Mitsubishi Electric Hydronics & IT Cooling Systems S.p.A. in Bassano del Grappa [IT] (January 2013 → February 2019).
• System specialist IT consultant, VB6software engineer and developer at Ergon in Castelfranco Veneto [IT] (July 2011 → December 2012).