Establishment of Standard Models Using Copula-Based Data Augmentation and Genetic Algorithms for Improving the Energy Performance of Small-Scale Aging Buildings

Simulation-dependent energy analysis has long dominated building retrofit research, yet this paradigm presents substantial barriers for non-expert building owners who lack technical software proficiency and detailed building documentation-a challenge compounded by the “curse of dimensionality” when multivariate analysis requires thousands of samples beyond available empirical records. Leveraging retrofit data accumulated through Korea’s Green Remodeling programs since 2017, this study proposes a Copula-Genetic Algorithm (Copula-GA) integrated framework that enables rational retrofit decision-making with minimal user inputs (construction year, floor area, structural type). From 178 documented retrofit cases, Gaussian copula-based multivariate sampling generated 10,000 synthetic records while preserving inter-variable dependency structures. Building physics constraints addressing vintage-thermal performance and capacity-efficiency relationships filtered implausible combinations, yielding 9898 valid cases with correlation matrix fidelity confirmed by a Frobenius norm deviation of 0.043. Evolutionary clustering employing a composite fitness function of Silhouette coefficient (0.68) and Davies-Bouldin Index (0.52) identified K = 16 as the optimal partition, categorizing outcomes into four reference model archetypes: Lightweight Structure (Type A, 27.0% reduction, 15.7-year payback), Masonry Structure (Type B, 29.0%, 14.8 years), RC Structure (Type C, 30.7%, 13.4 years), and Mixed Structure (Type D, 30.9%, 13.1 years). The proposed Copula-GA framework bridges the gap between advanced energy optimization methodologies and practical accessibility for non-expert building owners. By transforming limited empirical samples into reliable reference models, this research supports building-sector decarbonization. Using three minimal inputs, a building can be matched to one of the 16 standard models to obtain its expected saving rate, payback period, and recommended measures without detailed simulation.