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<p>Enhancing energy efficiency in buildings has become a key global priority. In this paper, a multi-objective optimization methodology was implemented to enhance three key objectives: energy consumption, life cycle cost, and thermal comfort. A typical Jordanian apartment was used as a case study, with design variables such as roof material, wall material and daylighting control type were defined using OpenStudio software. EnergyPlus was employed to simulate the apartment model and to define the three objectives. The simulation-based optimization system included text-based input and output files for developing various input parameter combinations. The optimization software jEPlus + EA, using the NSGA-II algorithm, was used to find the optimal solutions. Key optimization results were compared with the baseline model, and Pareto-optimal fronts were presented for the optimal solutions from the multi-objective optimization problem. The optimization results significantly improved the apartment model's performance, energy consumption in the test apartment model decreased by 28.5%. Life cycle cost and discomfort hours also decreased 17.11 and 8.36%, respectively. Although the accuracy of simulation outputs depends on the accuracy of the database, this optimization methodology can adjust the model to optimize various parameters and aspects of a building, offering significant advantages over previous systems that were designed for specific buildings and lacked flexibility for future use.</p>

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Multi objective design optimization of residential buildings: energy consumption, life cycle cost and thermal discomfort based on NSGA-II

  • 期刊论文

  • 发表日期：

    2025年7月16日

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  • Mohammad Aburabi’e,
  • Khaled Bataineh,
  • Yousef Al-Kabaha

摘要

Enhancing energy efficiency in buildings has become a key global priority. In this paper, a multi-objective optimization methodology was implemented to enhance three key objectives: energy consumption, life cycle cost, and thermal comfort. A typical Jordanian apartment was used as a case study, with design variables such as roof material, wall material and daylighting control type were defined using OpenStudio software. EnergyPlus was employed to simulate the apartment model and to define the three objectives. The simulation-based optimization system included text-based input and output files for developing various input parameter combinations. The optimization software jEPlus + EA, using the NSGA-II algorithm, was used to find the optimal solutions. Key optimization results were compared with the baseline model, and Pareto-optimal fronts were presented for the optimal solutions from the multi-objective optimization problem. The optimization results significantly improved the apartment model's performance, energy consumption in the test apartment model decreased by 28.5%. Life cycle cost and discomfort hours also decreased 17.11 and 8.36%, respectively. Although the accuracy of simulation outputs depends on the accuracy of the database, this optimization methodology can adjust the model to optimize various parameters and aspects of a building, offering significant advantages over previous systems that were designed for specific buildings and lacked flexibility for future use.