Energy-Constrained Indoor Air Quality Optimization for HVAC System in Smart Building

The heating, ventilation, air conditioning (HVAC) system is a common ventilation system applied to an indoor environment based on Internet of Things (IoT) technology. In HVAC, providing a comfortable temperature under the constraint of energy is a major challenge. In this article, we propose an air quality optimization strategy to control the air supply and energy consumption, and build several dynamic models to capture the stochastic processes in HVAC. Besides, a system utility maximization problem is formulated. We provide a solution framework based on the Lyapunov optimization method. Based on this framework, we propose a utility-optimal air quality optimization algorithm to solve the subproblem, and theoretically prove that it can achieve the near-optimal system utility. Additionally, the upper bound of the indoor temperature is derived, and the optimality of the algorithm is analyzed. Simulation results show the impact of the system parameter on the HVAC system and the indoor temperature, and verify that the proposed strategy and methods can maintain the comfortable temperature range and supply more fresh air effectively under the constraints of energy consumption.

Automated summary

This article proposes an air quality optimization strategy for HVAC systems based on IoT technology. By using dynamic models and the Lyapunov optimization method, the stochastic processes in HVAC systems can be captured and solved. Simulation results show that the proposed strategy and methods can effectively maintain a comfortable temperature range and provide more fresh air.