Simulation-Based Multi-Objective Optimization for Building Retrofits in Iran: Addressing Energy Consumption, Emissions, Comfort, and Indoor Air Quality Considering Climate Change

Abstract

Climate change poses significant challenges to energy efficiency and occupant comfort in residential buildings. This study introduces a simulation-based multi-objective optimization approach for architectural design, aimed at addressing these challenges and enhancing environmental sustainability. Utilizing EnergyPlus for energy simulations and jEPlus to identify objective functions and design parameters, the research employed the NSGA-II algorithm through jEPlus + EA for multi-objective optimization. A Morris sensitivity analysis assessed the impact of 25 design variables—including heating and cooling setpoints, air infiltration rates, insulation types, window selections, airflow rates, and HVAC systems—on key objective functions. Applied to a residential building in Sari, Iran, the study analyzed various climate change scenarios to minimize five main objectives: primary energy consumption, greenhouse gas emissions, indoor air quality, predicted percentage of dissatisfied, and visual discomfort hours. The weighted sum method was used to select optimal solutions from the Pareto front. Results demonstrated that the recommended energy retrofit strategies could reduce primary energy consumption by up to 60%, greenhouse gas emissions by 60%, predicted thermal dissatisfaction by 65%, and visual discomfort hours by 83%, while also achieving indoor air quality levels that meet ASHRAE recommended standards. However, the implementation of these energy-efficient solutions may require careful consideration of trade-offs in design decisions when addressing climate change challenges. © 2025 by the authors.