摘要
将时间序列分析方法应用到商业建筑能耗的分析和预测中,介绍了建筑能耗预测模型的建模方法,将逐月积温值、逐月相对湿度平均值、逐月工作日天数及逐月非工作日天数4个建筑逐月能耗的主要影响因子引入建筑能耗预测模型,根据逐月建筑能耗数据,建立基于时间序列分析并加入物理原理化处理的数据驱动模型,并进行检验与修正。应用该方法对3个商业建筑进行了实例分析,结果显示,对于逐月出租率基本不变的商业建筑,能耗预测结果较理想。
Applies the time series analysis method to analyses and prediction of energy consumption of commercial buildings,and presents the modeling method of the building energy consumption prediction model.Introduces the four main factors of influencing monthly energy consumption,i.e.monthly cumulative temperature value,monthly mean relative humidity value,monthly work days and monthly nonwork days into the building energy consumption prediction model.According to monthly building energy consumption data,establishes a data-driven model based on time series analysis and physical principle,and the model is modified and verified.Applies the method to three commercial buildings and the results show that for the commercial building with almost constant monthly occupancy rate,the energy consumption prediction result is better agreed with the actual data.
出处
《暖通空调》
北大核心
2013年第8期71-77,共7页
Heating Ventilating & Air Conditioning
关键词
时间序列
能耗预测
商业建筑
逐月积温值
逐月相对湿度平均值
逐月工作日天数
逐月非工作日天数
time series
energy consumption prediction
commercial building
monthly cumulative temperature value
monthly mean relative humidity value
monthly work days
monthly non-work days
