Optimization of an HVAC system with a particle swarm optimization algorithm

This paper addresses the issues of energy consumption reduction in existing buildings while providing comfort levels for inhabitants. Beside, representing an information-driven for the advancement of an HVAC(heating, ventilation, and air conditioning) system in an office building. The core of this work will be the application on a real case study (an office building) in which the mentioned objectives depend on a set of independent and control variables such as internal temperature, humidity, and the presence of people. In particular, this research will find the best configurations of the control settings derived from optimization of the model minimize energy consumption and maintaining optimal comfort levels. The solutions derived from the particle swarm optimization(PSO) algorithm point to a big number of control choices for an HVAC system, describing a range of trade-offs between energy consumption and thermal comfort.