Decentralized Optimization for Energy Saving of HVAC Systems

Improving the control strategy of building HVAC (heating, ventilation, and air-conditioning) systems can lead to significant energy savings while preserving human comfort requirements. This paper formulates the optimization problem to obtain the setpoints of control variables with the lowest HVAC system energy consumption. The optimization problem is nonlinear, strongly coupled, and has both discrete and continuous control variables. This paper proposes a decentralized optimization method to divide the HVAC system into multiple subsystems and then solve the subproblems based on the local information. Numerical results demonstrate that with limited knowledge of its neighbouring subsystems, each subsystem can achieve the local/global optimal solution of the original optimization problem. The method proposed in this paper has a broad application potential since it does not demand the global system knowledge.