Integrating a variety of renewable energy and waste heat resources, the district energy bus system (EBS) has become a core infrastructure for realizing building heating and cooling in the context of the current low-carbon energy transition. This paper focused on office buildings in hot summer and cold winter areas of China, and developed parameter sensitivity research based on correlation analysis and regression analysis with selected parameters. The results show that the sensitivities are different among the input and output parameters. In general, based on correlation analysis and regression analysis, surface water temperature, outlet temperature of surface water coils are the variables with the highest correlation degree with the output parameters. In addition, the cooling load has a higher correlation with the output parameters than the heating load. The results of this paper can be used for parameter selection in system optimization to help confirm the priority of parameters and reduce the uncertainty of model input and output parameters.
Keywords Energy Bus System (EBS), 5GDHC, office buildings, parameter sensitivity analysis