Research on optimal control of HVAC system using swarm intelligence algorithms.

Energy conservation in buildings is of vital importance for solving the problem of global warming and energy scarcity in today's world. In this paper, we discuss the optimal control methods of the heating, ventilation, and air-conditioning (HVAC) system using swarm intelligence algorithms to reduce energy consumption of buildings. The performances of ten optimization algorithms are compared. The results on test functions manifest the artificial bee colony algorithm (ABC) exhibits the best performance among the focused optimization algorithms. Taking a real HVAC system as an example, the holistic energy models of equipment in the HVAC system are established and validated. Then, the focused algorithms are used for the optimal control of a real HVAC system aiming at energy conservation. The simulated results based on 24-h real operation data show that the energy-saving ratio through by the ABC can reach 24.07% on average. The work in this study will contribute to the building energy conservation and carbon neutral development in the future. • The performances of ten swarm intelligence optimization algorithms on the test function are compared. • A holistic model of a real heating ventilation and air conditioning (HVAC) system is developed. • The performances of ten optimization algorithms in the holistic energy consumption model are discussed. • The artificial bee colony (ABC) algorithm is applied to a real air-conditioning system for typical daily analysis. [ABSTRACT FROM AUTHOR]