Abstract

Improving building energy efficiency is a major goal of energy policies. In recent years, various energy efficiency projects have been underway to reduce greenhouse gases. The general method of evaluating energy savings focuses on performance analysis of energy saving technologies. However, fluctuations in energy consumption of buildings can be caused by issues other than changes in specific energy saving facilities. Therefore, it is cost-effective to determine energy savings through changes in the overall building energy consumption before and after implementation of ECM (Energy Conservation Measures). Through this, we statistically verified a method of considering outdoor temperatures when calculating the energy savings using the energy efficiency measurement method IPMVP (International Performance Measurement and Verification Protocol). Based on this analysis, unlike methods that assume numerous data will be highly correlated, we found that our model considering the data resolutions of the average daily temperature and daily power consumption was the most suitable and efficient among the models with various data resolutions. This shows that statistically appropriate results can be obtained even if there is only small amounts of outdoor temperature and daily energy consumption data needed for energy savings assessment. It is expected that energy management methodologies for practitioners will improve if analysis methods considering energy consumption patterns of buildings are further developed.

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