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

Dongfang Yang; Ruiwei Qian; Xian Zhou

doi:10.1117/12.3025008

13 May 2024 Control strategy of central air-conditioning cooling system based on twin model game

Dongfang Yang, Ruiwei Qian, Xian Zhou

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315948 (2024) https://doi.org/10.1117/12.3025008
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dongfang Yang, Ruiwei Qian, and Xian Zhou "Control strategy of central air-conditioning cooling system based on twin model game", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315948 (13 May 2024); https://doi.org/10.1117/12.3025008

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