Author(s)

Ming Li, Jian Li

Corresponding Author

Ming Li

Abstract

Aiming at the problems of large load variation range, low overall efficiency and high energy consumption of central air conditioning, this paper proposes a data-based analysis method to optimize the control of the cooling water system and chiller in the central air conditioning system. By analyzing the operation characteristics of cooling water system equipment, different optimization algorithms were used to establish a data-driven prediction model. Through the optimization algorithm, random equipment combination was made, and finally a group of equipment start-stop combination was found, so that the system could meet the constraints and at the same time, the energy consumption was the lowest. The actual running data verify the feasibility and effectiveness of the method.

Keywords

Big data, Intelligent energy saving, Central air conditioning, Optimization algorithm