A Simplified Multi-Objective Optimization Method for Building Energy Design Under Present and Future Climate Scenarios

Climate change poses significant challenges for building energy retrofit, as solutions optimized for present-day conditions may become suboptimal under future climates. Although multi-objective optimization is an effective approach for identifying retrofit strategies, incorporating both present and future scenarios substantially increases computational cost. This study proposes a simplified multi-objective optimization method in which the genetic-algorithm search is performed only once, under present-day weather; the resulting Pareto-optimal solutions are then re-simulated under four future IPCC CMIP6 scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), reducing the required full optimization runs. The approach combines EnergyPlus for thermal simulation, Future Weather Generator for creating future weather files, and jEPlus+EA for NSGA-II optimization. The method was applied to a university residence in La Pampa, Argentina, optimizing wall, roof, and window retrofits for Annual Heating Load and Heat Index Safe Hours. The most robust solutions prevented heat gains—including ventilated façades, enhanced roof insulation, and heat-mirror glazing—achieving 29% and 36% increases in Safe Hours and heating load, respectively, versus the non-retrofitted building; however, they failed to maintain that performance under future climates. These findings demonstrate a useful method to include climate change in building energy retrofit design, ensuring its effectiveness under evolving climate conditions.