Control strategy of central air-conditioning cooling system based on twin model game

Abstract

The central off air-conditioning cold source system is a significant contributor to the overall energy consumption of the building body, which is dominated by the central air-conditioning system. Therefore, maximizing the central airconditioning energy efficiency requires improving the cold source system's energy efficiency. Based on these findings, we suggest a neural network data-driven method of energy-efficient control for the cold source system. To begin, operational data and equipment requirements for the cold source system were used to mimic operating circumstances. Then, the real data in the operational database was filtered with the help of the simulated data. Ultimately, the adjusted and standardized data model was implemented in the cold source system to optimize its efficiency. The experimental results successfully confirmed the data model's validity after validation.