IoT Based Architecture for Model Predictive Control of HVAC Systems in Smart Buildings

TLDR

Efficient HVAC management in smart buildings is a key IoT application, with MPC algorithms optimizing indoor comfort and energy consumption in a closed‑loop fashion. The paper proposes an IoT‑based architecture to implement MPC for HVAC systems in real environments. The architecture connects sensing, control, and actuating subsystems to the Internet, with sensors and actuators communicating via a remote database and control unit, enabling remote interface and set‑point adjustment, and is implemented and tested in a campus building at the Polytechnic of Bari. Real‑world testing demonstrates that the proposed MPC architecture improves thermal comfort and achieves energy savings compared to a classical thermostat.

Abstract

The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closed-loop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to end-users. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related set-points of the system; while comfort and environmental indices are transferred via the Internet and displayed on the end-users' interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach.