Control Strategies for Heating, Ventilation, Air-Conditioning Systems enhancing buildings energy efficiency

Today HVAC control systems play an essential role in energy efficient operation of buildings, demand response, renewables integration, and decision making of HVAC systems deployment and building construction. Hence, it will be vital to be aware of current trends driving research and innovation. The presentation, firstly, will demonstrate a literature review of today's scientific papers on various control strategies for heating, ventilation, and air-conditioning (HVAC) systems of different buildings. Particularly, rule-based control, model predictive control (MPC), and control based on reinforcement learning will be covered. In the second part of the work, the overview of the different control strategies available in the industry will be analyzed. Lastly, the comparison of these two reviews will be presented to access the relationship between industry and academia for further discussion and thinkings.


Arseniy Sleptsov, PhD student at Skoltech

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Arseniy received his Specialist degree in Life-Support Systems with honors in 2015 from Power Engineering Department at Bauman Moscow State Technical University. His thesis was dedicated to air-sourced heat pump for heating a building located in a remote area.

Further, Arseniy proceeded for a Master degree in Energy Systems in Skolkovo Institute of Science and Technology (Skoltech). His master thesis was about building energy modeling and energy efficiency improvement for Russian test case.

During his undergraduate and graduate studying, Arseniy received industrial experience, which consolidated his interest in sustainable energy, civil and environmental engineering, energy performance of buildings and urban energy systems. Arseniy had internships in such companies as R&D department of Gazprom-Neft, Energy Efficiency department at Federal Grid Company of United Power Systems of Russia. He also was awarded a scholarship at the University of Applied Sciences in Zittau to have summer research internship. Moreover, Arseniy has work experience in a Green Building consulting company.

Arseniy currently is a member of the working group of the Prof. Aldo Bischi. In particular, he is involved in building energy modeling, energy consumption and indoor climate optimization, model predictive control. He also studies Russian building stock energy consumption, technical solutions, and policies on energy efficiency improvements in buildings.

Research interests: building energy modeling, smart buildings, smart cities, district heating and cooling, smart grids, microgrids, control and optimization, data science, AI