一种基于数据驱动的空调系统能耗逐日评价指标
Data-driven daily evaluation index for air conditioning system energy consumption
摘要：
提出了一种新的空调系统能耗强度评价指标，即典型日单位面积空调能耗。使用k-means聚类算法对我国各个气候区典型城市夏季气象参数进行了聚类分析，发现我国不同气候区夏季供冷日气象参数可以聚类为6~7个典型日。利用现有典型气候区办公建筑逐日空调系统能耗历史数据，建立了比对数据库，得到典型日单位面积空调能耗为0.20~0.85 kW·h/(m2·d)，平均值为0.44 kW·h/(m2·d)。研究了日单位面积空调能耗随气象参数的变化规律。利用模拟软件研究了建筑热工性能、建筑内热源等参数对日单位面积空调能耗的影响，提出了修正方法。初步给出了空调系统能耗日评价指标，并应用于案例分析。
Abstract：
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.
Keywords:airconditioningsystem,energyconsumptionintensity,dailyevaluationindex,datadriving,clusteranalysisofmeteorologicalparameter