AUTHOR=Zhou Ying , Li Xinmei , Yang Dongfang 

TITLE=Optimization of Metro Central Air Conditioning Cold Source System Based on PCA-ANN Data Model

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.762275

DOI=10.3389/fenrg.2022.762275

ISSN=2296-598X

ABSTRACT=The energy saving of subway central air conditioning system has higher energy saving re-quirements than ordinary building energy saving, due to the special characteristics of its archi-tectural design and usage scenarios. The central air conditioning of metro stations is the main power-consuming equipment in metro stations, and its cooling source system occupies a large proportion. Therefore, energy-saving optimization of the cold source system is of key signifi-cance to the energy saving of the central air conditioning system. By analyzing the energy sav-ing potential, an energy saving control method for cold source systems using the PCA-ANN da-ta model is proposed. Firstly, the simulation of the operating condition was been done, based on the operating data and equipment parameters of the cold source system. Then, according to the simulation data, the effective operating data was been filtered from the operating database. In addition, the filtered dates were been analyzed by principal component analysis. Finally, the data model was been fitted and calibrated based on the filtered data, which was been used to guide the optimal operation of the cold source system. After applying the new method, the sys-tem energy consumption was been reduced by 10.5% in the whole month of August. Compared with the un-optimized energy parameters, the proposed method shows some advantages in en-ergy efficiency.