Data-driven daily evaluation index for air conditioning system energy consumption

Proposes a new energy consumption intensity evaluation index for air conditioning systems, that is, the typical daily air conditioning energy consumption per unit area. Performs cluster analysis on the summer meteorological parameters of typical cities in various climate zones in China using the k-means clustering algorithm. Finds that the meteorological parameters of summer cooling days in different climate zones in China can be clustered into 6-7 typical days. Using the historical data of daily air conditioning system energy consumption of office buildings in typical climate zones, establishes a comparison database, and obtains that the typical daily air conditioning energy consumption per unit area is 0.20-0.85 kWh/(m2·d), with an average of 0.44 kWh/(m2·d). Studies the variation of the daily air conditioning energy consumption per unit area with the meteorological parameters. Studies the influence of building thermal performance, building interior heat source and other parameters on the daily air conditioning energy consumption per unit area using simulation software, and proposes a correction method. Initially proposes the daily evaluation index of energy consumption of the air conditioning system, and applies it to the case analysis.