Energy performance evaluation of existing buildings is commonly based on annual energy consumption or Energy Use Intensity (EUI). While EUI effectively represents the magnitude of energy use, it has limitations in capturing differences in operational and management performance. Detailed equipment-level or control data required for operational assessment are rarely available for most existing buildings, necessitating alternative approaches based on publicly accessible data. This study proposes a set of supplementary indicators for the relative diagnosis of operational and management performance in existing residential apartment buildings using publicly available electricity consumption data in Korea. Instead of focusing on absolute energy use levels, the proposed approach analyzes temporal energy use patterns to infer operational characteristics. Three indicators are introduced: the Operational Stability Index (OSI), which evaluates monthly consumption variability; the Seasonal Suitability Indicator (SSI), which assesses the appropriateness of seasonal operation; and the Abnormal Signal Index (ASI), which quantifies the frequency of statistically significant anomalies in hourly energy use. These indicators were applied to government-leased apartment buildings where data availability was limited. The results show that buildings with similar EUI values can exhibit different levels of operational stability and seasonal consistency. While ASI values exhibited limited variation among the analyzed buildings, this finding may reflect operational homogeneity rather than low indicator effectiveness. The proposed indicators are not absolute performance metrics, but rather diagnostic tools that complement conventional EUI-based evaluations. By revealing temporal usage patterns and variability that are not captured by aggregate energy indicators, the framework provides foundational information for relatively identifying buildings with atypical or potentially inefficient operational behavior under current public data constraints.
Choi et al. (Tue,) studied this question.