Integrating Energy Benchmarks and Distributional Fairness to Support Retrofit Prioritization in Old Residential Buildings

Energy-efficiency retrofit assessment for old residential buildings commonly relies on energy benchmarks, but such benchmarks cannot reveal household-level disparities in energy use. This study integrates energy-consumption benchmarks with distributional-fairness indicators to support retrofit prioritization. Monitored electricity data from 1024 households in four representative old residential building types in Chongqing were analyzed using the Dagum Gini coefficient decomposition method. The results show clear seasonal and typological differences in energy-use imbalance. The annual Gini coefficients for Types A–D were 0.34, 0.42, 0.45, and 0.40, respectively, while the overall level of imbalance generally followed the order winter > summer > transition seasons > annual average. Median energy use intensity (EUI) did not correspond directly to distributional fairness. Type B had the highest annual median EUI (3.89 kWh/m2) but not the highest Gini coefficient, whereas Type C had the lowest median EUI (3.28 kWh/m2) and the highest Gini coefficient (0.45). These findings show that benchmark-based assessment alone may misidentify retrofit priorities. A dual-benchmark diagnostic framework is therefore proposed to integrate energy-use level and distributional fairness, supporting more precise retrofit prioritization, fairer resource allocation, and sustainable renewal of old residential communities.