A Decentralized Swarm Intelligence Algorithm for Global Optimization of HVAC System

Abstract

To solve the high labor and maintenance cost while save energy problems in actual engineering, a decentralized control structure and optimization method for the heating, ventilation, and air conditioning (HVAC) systems are proposed. In this decentralized HVAC control system, each updated smart equipment is connected according to the physical correlations and can communicate with adjacent nodes collaboratively. Furthermore, a novel fully distributed and self-organizing swarm intelligence optimization algorithm is presented. And the algorithm runs in each smart equipment to achieve the optimal operation and avoid the conflict among correlated equipment. Moreover, the convergence property of the novel method is analyzed theoretically. This method is confirmed effective for realizing the global optimal operation of HVAC system through simulation results and hardware tests on actual engineering.